Topic Keywords

[ $\ell_1$ norm ] [ $f-$divergence ] [ 3D Convolution ] [ 3D deep learning ] [ 3D generation ] [ 3d point cloud ] [ 3D Reconstruction ] [ 3D scene understanding ] [ 3D shape representations ] [ 3D shapes learning ] [ 3D vision ] [ 3D Vision ] [ abstract reasoning ] [ abstract rules ] [ Acceleration ] [ accuracy ] [ acoustic condition modeling ] [ Action localization ] [ action recognition ] [ activation maximization ] [ activation strategy. ] [ Active learning ] [ Active Learning ] [ AdaBoost ] [ adaptive heavy-ball methods ] [ Adaptive Learning ] [ adaptive methods ] [ adaptive optimization ] [ ADMM ] [ Adversarial Accuracy ] [ Adversarial Attack ] [ Adversarial Attacks ] [ adversarial attacks/defenses ] [ Adversarial computer programs ] [ Adversarial Defense ] [ Adversarial Example Detection ] [ Adversarial Examples ] [ Adversarial Learning ] [ Adversarial Machine Learning ] [ adversarial patch ] [ Adversarial robustness ] [ Adversarial Robustness ] [ Adversarial training ] [ Adversarial Training ] [ Adversarial Transferability ] [ aesthetic assessment ] [ affine parameters ] [ age estimation ] [ Aggregation Methods ] [ AI for earth science ] [ ALFRED ] [ Algorithm ] [ algorithmic fairness ] [ Algorithmic fairness ] [ Algorithms ] [ alignment ] [ alignment of semantic and visual space ] [ amortized inference ] [ Analogies ] [ annotation artifacts ] [ anomaly-detection ] [ Anomaly detection with deep neural networks ] [ anonymous walk ] [ appearance transfer ] [ approximate constrained optimization ] [ approximation ] [ Approximation ] [ Architectures ] [ argoverse ] [ Artificial Integlligence ] [ ASR ] [ assistive technology ] [ associative memory ] [ Associative Memory ] [ asynchronous parallel algorithm ] [ Atari ] [ Attention ] [ Attention Mechanism ] [ Attention Modules ] [ attractors ] [ attributed walks ] [ Auction Theory ] [ audio understanding ] [ Audio-Visual ] [ audio visual learning ] [ audio-visual representation ] [ audio-visual representation learning ] [ Audio-visual sound separation ] [ audiovisual synthesis ] [ augmented deep reinforcement learning ] [ autodiff ] [ Autoencoders ] [ automated data augmentation ] [ automated machine learning ] [ automatic differentiation ] [ AutoML ] [ autonomous learning ] [ autoregressive language model ] [ Autoregressive Models ] [ AutoRL ] [ auxiliary information ] [ auxiliary latent variable ] [ Auxiliary Learning ] [ auxiliary task ] [ Average-case Analysis ] [ aversarial examples ] [ avoid knowledge leaking ] [ backdoor attack ] [ Backdoor Attacks ] [ Backdoor Defense ] [ Backgrounds ] [ backprop ] [ back translation ] [ backward error analysis ] [ bagging ] [ batchnorm ] [ Batch Normalization ] [ batch reinforcement learning ] [ Batch Reinforcement Learning ] [ batch selection ] [ Bayesian ] [ Bayesian classification ] [ Bayesian inference ] [ Bayesian Inference ] [ Bayesian networks ] [ Bayesian Neural Networks ] [ behavior cloning ] [ belief-propagation ] [ Benchmark ] [ benchmarks ] [ benign overfitting ] [ bert ] [ BERT ] [ beta-VAE ] [ better generalization ] [ biased sampling ] [ biases ] [ Bias in Language Models ] [ bidirectional ] [ bilevel optimization ] [ Bilinear games ] [ Binary Embeddings ] [ Binary Neural Networks ] [ binaural audio ] [ binaural speech ] [ biologically plausible ] [ Biometrics ] [ bisimulation ] [ Bisimulation ] [ bisimulation metrics ] [ bit-flip ] [ bit-level sparsity ] [ blind denoising ] [ blind spots ] [ block mdp ] [ boosting ] [ bottleneck ] [ bptt ] [ branch and bound ] [ Brownian motion ] [ Budget-Aware Pruning ] [ Budget constraints ] [ Byzantine resilience ] [ Byzantine SGD ] [ CAD modeling ] [ calibration ] [ Calibration ] [ calibration measure ] [ cancer research ] [ Capsule Networks ] [ Catastrophic forgetting ] [ Catastrophic Forgetting ] [ Causal Inference ] [ Causality ] [ Causal network ] [ certificate ] [ certified defense ] [ Certified Robustness ] [ challenge sets ] [ change of measure ] [ change point detection ] [ channel suppressing ] [ Channel Tensorization ] [ Channel-Wise Approximated Activation ] [ Chaos ] [ chebyshev polynomial ] [ checkpointing ] [ Checkpointing ] [ chemistry ] [ CIFAR ] [ Classification ] [ class imbalance ] [ clean-label ] [ Clustering ] [ Clusters ] [ CNN ] [ CNNs ] [ Code Compilation ] [ Code Representations ] [ Code Structure ] [ code summarization ] [ Code Summarization ] [ Cognitively-inspired Learning ] [ cold posteriors ] [ collaborative learning ] [ Combinatorial optimization ] [ common object counting ] [ commonsense question answering ] [ Commonsense Reasoning ] [ Communication Compression ] [ co-modulation ] [ complete verifiers ] [ complex query answering ] [ Composition ] [ compositional generalization ] [ compositional learning ] [ compositional task ] [ Compressed videos ] [ Compressing Deep Networks ] [ Compression ] [ computation ] [ computational biology ] [ Computational Biology ] [ computational complexity ] [ Computational imaging ] [ Computational neuroscience ] [ Computational resources ] [ computer graphics ] [ Computer Vision ] [ concentration ] [ Concentration of Measure ] [ Concept-based Explanation ] [ concept drift ] [ Concept Learning ] [ conditional expectation ] [ Conditional GANs ] [ Conditional Generation ] [ Conditional generative adversarial networks ] [ conditional layer normalization ] [ Conditional Neural Processes ] [ Conditional Risk Minimization ] [ Conditional Sampling ] [ conditional text generation ] [ Conferrability ] [ confidentiality ] [ conformal inference ] [ conformal prediction ] [ conjugacy ] [ conservation law ] [ consistency ] [ consistency training ] [ Consistency Training ] [ constellation models ] [ constrained beam search ] [ Constrained optimization ] [ constrained RL ] [ constraints ] [ constraint satisfaction ] [ contact tracing ] [ Contextual Bandits ] [ Contextual embedding space ] [ Continual learning ] [ Continual Learning ] [ continuation method ] [ continuous and scalar conditions ] [ continuous case ] [ Continuous Control ] [ continuous convolution ] [ continuous games ] [ continuous normalizing flow ] [ continuous time ] [ Continuous-time System ] [ continuous treatment effect ] [ contrastive divergence ] [ Contrastive learning ] [ Contrastive Learning ] [ Contrastive Methods ] [ contrastive representation learning ] [ control barrier function ] [ controlled generation ] [ Controlled NLG ] [ Convergence ] [ Convergence Analysis ] [ convex duality ] [ Convex optimization ] [ ConvNets ] [ convolutional kernel methods ] [ Convolutional Layer ] [ convolutional models ] [ Convolutional Networks ] [ copositive programming ] [ corruptions ] [ COST ] [ Counterfactual inference ] [ counterfactuals ] [ Counterfactuals ] [ covariant neural networks ] [ covid-19 ] [ COVID-19 ] [ Cross-domain ] [ cross-domain few-shot learning ] [ cross-domain video generation ] [ cross-episode attention ] [ cross-fitting ] [ cross-lingual pretraining ] [ Cryptographic inference ] [ cultural transmission ] [ Curriculum Learning ] [ curse of memory ] [ curvature estimates ] [ custom voice ] [ cycle-consistency regularization ] [ cycle-consistency regularizer ] [ DAG ] [ DARTS stability ] [ Data augmentation ] [ Data Augmentation ] [ data cleansing ] [ Data-driven modeling ] [ data-efficient learning ] [ data-efficient RL ] [ Data Flow ] [ data labeling ] [ data parallelism ] [ Data Poisoning ] [ Data Protection ] [ Dataset ] [ dataset bias ] [ dataset compression ] [ dataset condensation ] [ dataset corruption ] [ dataset distillation ] [ dataset summarization ] [ data structures ] [ debiased training ] [ debugging ] [ Decentralized Optimization ] [ decision boundary geometry ] [ decision trees ] [ declarative knowledge ] [ deep-anomaly-detection ] [ Deep Architectures ] [ Deep denoising priors ] [ deep embedding ] [ Deep Ensembles ] [ deep equilibrium models ] [ Deep Equilibrium Models ] [ Deepfake ] [ deep FBSDEs ] [ Deep Gaussian Processes ] [ Deep generative model ] [ Deep generative modeling ] [ Deep generative models ] [ deeplearning ] [ Deep learning ] [ Deep Learning ] [ deep learning dynamics ] [ Deep Learning Theory ] [ deep network training ] [ deep neural network ] [ deep neural networks. ] [ Deep Neural Networks ] [ deep one-class classification ] [ deep Q-learning ] [ Deep reinforcement learning ] [ Deep Reinforcement Learning ] [ deep ReLU networks ] [ Deep residual neural networks ] [ deep RL ] [ deep sequence model ] [ deepset ] [ Deep Sets ] [ Deformation Modeling ] [ delay ] [ Delay differential equations ] [ denoising score matching ] [ Dense Retrieval ] [ Density estimation ] [ Density Estimation ] [ Density ratio estimation ] [ dependency based method ] [ deployment-efficiency ] [ depression ] [ depth separation ] [ descent ] [ description length ] [ determinantal point processes ] [ Device Placement ] [ dialogue state tracking ] [ differentiable optimization ] [ Differentiable physics ] [ Differentiable Physics ] [ Differentiable program generator ] [ differentiable programming ] [ Differentiable rendering ] [ Differentiable simulation ] [ differential dynamica programming ] [ differential equations ] [ Differential Geometry ] [ differentially private deep learning ] [ Differential Privacy ] [ diffusion probabilistic models ] [ diffusion process ] [ dimension ] [ Directed Acyclic Graphs ] [ Dirichlet form ] [ Discrete Optimization ] [ discretization error ] [ disentangled representation learning ] [ Disentangled representation learning ] [ Disentanglement ] [ distance ] [ Distillation ] [ distinct elements ] [ Distributed ] [ distributed deep learning ] [ distributed inference ] [ Distributed learning ] [ distributed machine learning ] [ Distributed ML ] [ Distributed Optimization ] [ distributional robust optimization ] [ distribution estimation ] [ distribution shift ] [ diverse strategies ] [ diverse video generation ] [ Diversity denoising ] [ Diversity Regularization ] [ DNN ] [ DNN compression ] [ document analysis ] [ document classification ] [ document retrieval ] [ domain adaptation theory ] [ Domain Adaption ] [ Domain Generalization ] [ domain randomization ] [ Domain Translation ] [ double descent ] [ Double Descent ] [ doubly robustness ] [ Doubly-weighted Laplace operator ] [ Dropout ] [ drug discovery ] [ Drug discovery ] [ dst ] [ Dual-mode ASR ] [ Dueling structure ] [ Dynamical Systems ] [ dynamic computation graphs ] [ dynamics ] [ dynamics prediction ] [ dynamic systems ] [ Early classification ] [ Early pruning ] [ early stopping ] [ EBM ] [ Edit ] [ EEG ] [ effective learning rate ] [ Efficiency ] [ Efficient Attention Mechanism ] [ efficient deep learning ] [ Efficient Deep Learning ] [ Efficient Deep Learning Inference ] [ Efficient ensembles ] [ efficient inference ] [ efficient inference methods ] [ Efficient Inference Methods ] [ EfficientNets ] [ efficient network ] [ Efficient Networks ] [ Efficient training ] [ Efficient Training ] [ efficient training and inference. ] [ egocentric ] [ eigendecomposition ] [ Eigenspectrum ] [ ELBO ] [ electroencephalography ] [ EM ] [ Embedding Models ] [ Embedding Size ] [ Embodied Agents ] [ embodied vision ] [ emergent behavior ] [ empirical analysis ] [ Empirical Game Theory ] [ empirical investigation ] [ Empirical Investigation ] [ empirical study ] [ empowerment ] [ Encoder layer fusion ] [ end-to-end entity linking ] [ End-to-End Object Detection ] [ Energy ] [ Energy-Based GANs ] [ energy based model ] [ energy-based model ] [ Energy-based model ] [ energy based models ] [ Energy-based Models ] [ Energy Based Models ] [ Energy-Based Models ] [ Energy Score ] [ ensemble ] [ Ensemble ] [ ensemble learning ] [ ensembles ] [ Ensembles ] [ entity disambiguation ] [ entity linking ] [ entity retrieval ] [ entropic algorithms ] [ Entropy Maximization ] [ Entropy Model ] [ entropy regularization ] [ epidemiology ] [ episode-level pretext task ] [ episodic training ] [ equilibrium ] [ equivariant ] [ equivariant neural network ] [ ERP ] [ Evaluation ] [ evaluation of interpretability ] [ Event localization ] [ evolution ] [ Evolutionary algorithm ] [ Evolutionary Algorithm ] [ Evolutionary Algorithms ] [ Excess risk ] [ experience replay buffer ] [ experimental evaluation ] [ Expert Models ] [ Explainability ] [ explainable ] [ Explainable AI ] [ Explainable Model ] [ explaining decision-making ] [ explanation method ] [ explanations ] [ Explanations ] [ Exploration ] [ Exponential Families ] [ exponential tilting ] [ exposition ] [ external memory ] [ Extrapolation ] [ extremal sector ] [ facial recognition ] [ factor analysis ] [ factored MDP ] [ Factored MDP ] [ fairness ] [ Fairness ] [ faithfulness ] [ fast DNN inference ] [ fast learning rate ] [ fast-mapping ] [ fast weights ] [ FAVOR ] [ Feature Attribution ] [ feature propagation ] [ features ] [ feature visualization ] [ Feature Visualization ] [ Federated learning ] [ Federated Learning ] [ Few Shot ] [ few-shot concept learning ] [ few-shot domain generalization ] [ Few-shot learning ] [ Few Shot Learning ] [ fine-tuning ] [ finetuning ] [ Fine-tuning ] [ Finetuning ] [ fine-tuning stability ] [ Fingerprinting ] [ First-order Methods ] [ first-order optimization ] [ fisher ratio ] [ flat minima ] [ Flexibility ] [ flow graphs ] [ Fluid Dynamics ] [ Follow-the-Regularized-Leader ] [ Formal Verification ] [ forward mode ] [ Fourier Features ] [ Fourier transform ] [ framework ] [ Frobenius norm ] [ from-scratch ] [ frontend ] [ fruit fly ] [ fully-connected ] [ Fully-Connected Networks ] [ future frame generation ] [ future link prediction ] [ fuzzy tiling activation function ] [ Game Decomposition ] [ Game Theory ] [ GAN ] [ GAN compression ] [ GANs ] [ Garbled Circuits ] [ Gaussian Copula ] [ Gaussian Graphical Model ] [ Gaussian Isoperimetric Inequality ] [ Gaussian mixture model ] [ Gaussian process ] [ Gaussian Process ] [ Gaussian Processes ] [ gaussian process priors ] [ GBDT ] [ generalisation ] [ Generalization ] [ Generalization Bounds ] [ generalization error ] [ Generalization Measure ] [ Generalization of Reinforcement Learning ] [ generalized ] [ generalized Girsanov theorem ] [ Generalized PageRank ] [ Generalized zero-shot learning ] [ Generation ] [ Generative Adversarial Network ] [ Generative Adversarial Networks ] [ generative art ] [ Generative Flow ] [ Generative Model ] [ Generative modeling ] [ Generative Modeling ] [ generative modelling ] [ Generative Modelling ] [ Generative models ] [ Generative Models ] [ genetic programming ] [ Geodesic-Aware FC Layer ] [ geometric ] [ Geometric Deep Learning ] [ G-invariance regularization ] [ global ] [ global optima ] [ Global Reference ] [ glue ] [ GNN ] [ GNNs ] [ goal-conditioned reinforcement learning ] [ goal-conditioned RL ] [ goal reaching ] [ gradient ] [ gradient alignment ] [ Gradient Alignment ] [ gradient boosted decision trees ] [ gradient boosting ] [ gradient decomposition ] [ Gradient Descent ] [ gradient descent-ascent ] [ gradient flow ] [ Gradient flow ] [ gradient flows ] [ gradient redundancy ] [ Gradient stability ] [ Grammatical error correction ] [ Granger causality ] [ Graph ] [ graph classification ] [ graph coarsening ] [ Graph Convolutional Network ] [ Graph Convolutional Neural Networks ] [ graph edit distance ] [ Graph Generation ] [ Graph Generative Model ] [ graph-level prediction ] [ graph networks ] [ Graph neural network ] [ Graph Neural Network ] [ Graph neural networks ] [ Graph Neural Networks ] [ Graph pooling ] [ graph representation learning ] [ Graph representation learning ] [ Graph Representation Learning ] [ graph shift operators ] [ graph-structured data ] [ graph structure learning ] [ Greedy Learning ] [ grid cells ] [ grounding ] [ group disparities ] [ group equivariance ] [ Group Equivariance ] [ Group Equivariant Convolution ] [ group equivariant self-attention ] [ group equivariant transformers ] [ group sparsity ] [ Group-supervised learning ] [ gumbel-softmax ] [ Hamiltonian systems ] [ hard-label attack ] [ hard negative mining ] [ hard negative sampling ] [ Hardware-Aware Neural Architecture Search ] [ Harmonic Analysis ] [ harmonic distortion analysis ] [ healthcare ] [ Healthcare ] [ heap allocation ] [ Hessian matrix ] [ Heterogeneity ] [ Heterogeneous ] [ heterogeneous data ] [ Heterogeneous data ] [ Heterophily ] [ heteroscedasticity ] [ heuristic search ] [ hidden-parameter mdp ] [ hierarchical contrastive learning ] [ Hierarchical Imitation Learning ] [ Hierarchical Multi-Agent Learning ] [ Hierarchical Networks ] [ Hierarchical Reinforcement Learning ] [ Hierarchy-Aware Classification ] [ high-dimensional asymptotics ] [ high-dimensional statistic ] [ high-resolution video generation ] [ hindsight relabeling ] [ histogram binning ] [ historical color image classification ] [ HMC ] [ homomorphic encryption ] [ Homophily ] [ Hopfield layer ] [ Hopfield networks ] [ Hopfield Networks ] [ human-AI collaboration ] [ human cognition ] [ human-computer interaction ] [ human preferences ] [ human psychophysics ] [ humans in the loop ] [ hybrid systems ] [ Hyperbolic ] [ hyperbolic deep learning ] [ Hyperbolic Geometry ] [ hypercomplex representation learning ] [ hypergradients ] [ Hypernetworks ] [ hyperparameter ] [ Hyperparameter Optimization ] [ Hyper-Parameter Optimization ] [ HYPERPARAMETER OPTIMIZATION ] [ Image Classification ] [ image completion ] [ Image compression ] [ Image Editing ] [ Image Generation ] [ Image manipulation ] [ Image Modeling ] [ ImageNet ] [ image reconstruction ] [ Image segmentation ] [ Image Synthesis ] [ image-to-action learning ] [ Image-to-Image Translation ] [ image translation ] [ image warping ] [ imbalanced learning ] [ Imitation Learning ] [ Impartial Learning ] [ implicit bias ] [ Implicit Bias ] [ Implicit Deep Learning ] [ implicit differentiation ] [ implicit functions ] [ implicit neural representations ] [ Implicit Neural Representations ] [ Implicit Representation ] [ Importance Weighting ] [ impossibility ] [ incoherence ] [ Incompatible Environments ] [ Incremental Tree Transformations ] [ independent component analysis ] [ indirection ] [ Individual mediation effects ] [ Inductive Bias ] [ inductive biases ] [ inductive representation learning ] [ infinitely wide neural network ] [ Infinite-Width Limit ] [ infinite-width networks ] [ influence functions ] [ Influence Functions ] [ Information bottleneck ] [ Information Bottleneck ] [ Information Geometry ] [ information-theoretical probing ] [ Information theory ] [ Information Theory ] [ Initialization ] [ input-adaptive multi-exit neural networks ] [ input convex neural networks ] [ input-convex neural networks ] [ InstaHide ] [ Instance adaptation ] [ instance-based label noise ] [ Instance learning ] [ Instance-wise Learning ] [ Instrumental Variable Regression ] [ integral probability metric ] [ intention ] [ interaction networks ] [ Interactions ] [ interactive fiction ] [ Internet of Things ] [ Interpolation Peak ] [ Interpretability ] [ interpretable latent representation ] [ Interpretable Machine Learning ] [ interpretable policy learning ] [ in-the-wild data ] [ Intrinsically Motivated Reinforcement Learning ] [ Intrinsic Motivation ] [ intrinsic motivations ] [ Intrinsic Reward ] [ Invariance and Equivariance ] [ invariance penalty ] [ invariances ] [ Invariant and equivariant deep networks ] [ Invariant Representations ] [ invariant risk minimization ] [ Invariant subspaces ] [ inverse graphics ] [ Inverse reinforcement learning ] [ Inverse Reinforcement Learning ] [ Inverted Index ] [ irl ] [ IRM ] [ irregularly spaced time series ] [ irregular-observed data modelling ] [ isometric ] [ Isotropy ] [ iterated learning ] [ iterative training ] [ JEM ] [ Johnson-Lindenstrauss Transforms ] [ kernel ] [ Kernel Learning ] [ kernel method ] [ kernel-ridge regression ] [ kernels ] [ keypoint localization ] [ Knowledge distillation ] [ Knowledge Distillation ] [ Knowledge factorization ] [ Knowledge Graph Reasoning ] [ knowledge uncertainty ] [ Kullback-Leibler divergence ] [ Kurdyka-Łojasiewicz geometry ] [ label noise robustness ] [ Label Representation ] [ Label shift ] [ label smoothing ] [ Langevin dynamics ] [ Langevin sampling ] [ Language Grounding ] [ Language Model ] [ Language modeling ] [ Language Modeling ] [ Language Modelling ] [ Language Model Pre-training ] [ language processing ] [ language-specific modeling ] [ Laplace kernel ] [ Large-scale ] [ Large-scale Deep Learning ] [ large scale learning ] [ Large-scale Machine Learning ] [ large-scale pre-trained language models ] [ large-scale training ] [ large vocabularies ] [ Last-iterate Convergence ] [ Latency-aware Neural Architecture Search ] [ Latent Simplex ] [ latent space of GANs ] [ Latent Variable Models ] [ lattices ] [ Layer order ] [ layerwise sparsity ] [ learnable ] [ learned algorithms ] [ Learned compression ] [ learned ISTA ] [ Learning ] [ learning action representations ] [ learning-based ] [ learning dynamics ] [ Learning Dynamics ] [ Learning in Games ] [ learning mechanisms ] [ Learning physical laws ] [ Learning Theory ] [ Learning to Hash ] [ learning to optimize ] [ Learning to Optimize ] [ learning to rank ] [ Learning to Rank ] [ learning to teach ] [ learning with noisy labels ] [ Learning with noisy labels ] [ library ] [ lifelong ] [ Lifelong learning ] [ Lifelong Learning ] [ lifted inference ] [ likelihood-based models ] [ likelihood-free inference ] [ limitations ] [ limited data ] [ linear bandits ] [ Linear Convergence ] [ linear estimator ] [ Linear Regression ] [ linear terms ] [ linformer ] [ Lipschitz constants ] [ Lipschitz constrained networks ] [ Local Explanations ] [ locality sensitive hashing ] [ Locally supervised training ] [ local Rademacher complexity ] [ log-concavity ] [ Logic ] [ Logic Rules ] [ logsignature ] [ Long-Tailed Recognition ] [ long-tail learning ] [ Long-term dependencies ] [ long-term prediction ] [ long-term stability ] [ loss correction ] [ Loss function search ] [ Loss Function Search ] [ lossless source compression ] [ Lottery Ticket ] [ Lottery Ticket Hypothesis ] [ lottery tickets ] [ low-dimensional structure ] [ lower bound ] [ lower bounds ] [ Low-latency ASR ] [ low precision training ] [ low rank ] [ low-rank approximation ] [ low-rank tensors ] [ L-smoothness ] [ LSTM ] [ Lyapunov Chaos ] [ Machine learning ] [ Machine Learning ] [ machine learning for code ] [ Machine Learning for Robotics ] [ Machine Learning (ML) for Programming Languages (PL)/Software Engineering (SE) ] [ machine learning systems ] [ Machine translation ] [ Machine Translation ] [ magnitude-based pruning ] [ Manifold clustering ] [ Manifolds ] [ Many-task ] [ mapping ] [ Markov chain Monte Carlo ] [ Markov Chain Monte Carlo ] [ Markov jump process ] [ Masked Reconstruction ] [ mathematical reasoning ] [ Matrix and Tensor Factorization ] [ matrix completion ] [ matrix decomposition ] [ Matrix Factorization ] [ max-margin ] [ MCMC ] [ MCMC sampling ] [ mean estimation ] [ mean-field dynamics ] [ mean separation ] [ Mechanism Design ] [ medical time series ] [ mel-filterbanks ] [ memorization ] [ Memorization ] [ Memory ] [ memory efficient ] [ memory efficient training ] [ Memory Mapping ] [ memory optimized training ] [ Memory-saving ] [ mesh ] [ Message Passing ] [ Message Passing GNNs ] [ meta-gradients ] [ Meta-learning ] [ Meta Learning ] [ Meta-Learning ] [ Metric Surrogate ] [ minimax optimal rate ] [ Minimax Optimization ] [ minimax risk ] [ Minmax ] [ min-max optimization ] [ mirror-prox ] [ Missing Data Inference ] [ Missing value imputation ] [ Missing Values ] [ misssing data ] [ mixed precision ] [ Mixed Precision ] [ Mixed-precision quantization ] [ mixture density nets ] [ mixture of experts ] [ mixup ] [ Mixup ] [ MixUp ] [ MLaaS ] [ MoCo ] [ Model Attribution ] [ model-based control ] [ model-based learning ] [ Model-based Reinforcement Learning ] [ Model-Based Reinforcement Learning ] [ model-based RL ] [ Model-based RL ] [ Model Biases ] [ Model compression ] [ model extraction ] [ model fairness ] [ Model Inversion ] [ model order reduction ] [ model ownership ] [ model predictive control ] [ model-predictive control ] [ Model Predictive Control ] [ Model privacy ] [ Models for code ] [ models of learning and generalization ] [ Model stealing ] [ Modern Hopfield Network ] [ modern Hopfield networks ] [ modified equation analysis ] [ modular architectures ] [ Modular network ] [ modular networks ] [ modular neural networks ] [ modular representations ] [ modulated convolution ] [ Molecular conformation generation ] [ molecular design ] [ Molecular Dynamics ] [ molecular graph generation ] [ Molecular Representation ] [ Molecule Design ] [ Momentum ] [ momentum methods ] [ momentum optimizer ] [ monotonicity ] [ Monte Carlo ] [ Monte-Carlo tree search ] [ Monte Carlo Tree Search ] [ morphology ] [ Morse theory ] [ mpc ] [ Multi-agent ] [ Multi-agent games ] [ Multiagent Learning ] [ multi-agent platform ] [ Multi-Agent Policy Gradients ] [ Multi-agent reinforcement learning ] [ Multi-agent Reinforcement Learning ] [ Multi-Agent Reinforcement Learning ] [ Multi-Agent Transfer Learning ] [ multiclass classification ] [ multi-dimensional discrete action spaces ] [ Multi-domain ] [ multi-domain disentanglement ] [ multi-head attention ] [ Multi-Hop ] [ multi-hop question answering ] [ Multi-hop Reasoning ] [ Multilingual Modeling ] [ multilingual representations ] [ multilingual transformer ] [ multilingual translation ] [ Multimodal ] [ Multi-Modal ] [ Multimodal Attention ] [ multi-modal learning ] [ Multimodal Learning ] [ Multi-Modal Learning ] [ Multimodal Spaces ] [ Multi-objective optimization ] [ multi-player ] [ Multiplicative Weights Update ] [ Multi-scale Representation ] [ multitask ] [ Multi-task ] [ Multi-task Learning ] [ Multi Task Learning ] [ Multi-Task Learning ] [ multi-task learning theory ] [ Multitask Reinforcement Learning ] [ Multi-view Learning ] [ Multi-View Learning ] [ Multi-view Representation Learning ] [ Mutual Information ] [ MuZero ] [ Named Entity Recognition ] [ NAS ] [ nash ] [ natural gradient descent ] [ Natural Language Processing ] [ natural scene statistics ] [ natural sparsity ] [ Negative Sampling ] [ negotiation ] [ nested optimization ] [ network architecture ] [ Network Architecture ] [ Network Inductive Bias ] [ network motif ] [ Network pruning ] [ Network Pruning ] [ networks ] [ network trainability ] [ network width ] [ Neural Architecture Search ] [ Neural Attention Distillation ] [ neural collapse ] [ Neural data compression ] [ Neural IR ] [ neural kernels ] [ neural link prediction ] [ Neural Model Explanation ] [ neural module network ] [ Neural Network ] [ Neural Network Bounding ] [ neural network calibration ] [ Neural Network Gaussian Process ] [ neural network robustness ] [ Neural networks ] [ Neural Networks ] [ neural network training ] [ Neural Network Verification ] [ neural ode ] [ Neural ODE ] [ Neural ODEs ] [ Neural operators ] [ Neural Physics Engines ] [ Neural Processes ] [ neural reconstruction ] [ neural sound synthesis ] [ neural spike train ] [ neural symbolic reasoning ] [ neural tangent kernel ] [ Neural tangent kernel ] [ Neural Tangent Kernel ] [ neural tangent kernels ] [ Neural text decoding ] [ neurobiology ] [ Neuroevolution ] [ Neuro symbolic ] [ Neuro-Symbolic Learning ] [ neuro-symbolic models ] [ NLI ] [ NLP ] [ Node Embeddings ] [ noise contrastive estimation ] [ Noise-contrastive learning ] [ Noise model ] [ noise robust learning ] [ Noisy Demonstrations ] [ noisy label ] [ Noisy Label ] [ Noisy Labels ] [ Non-asymptotic Confidence Intervals ] [ non-autoregressive generation ] [ nonconvex ] [ non-convex learning ] [ Non-Convex Optimization ] [ Non-IID ] [ nonlinear control theory ] [ nonlinear dynamical systems ] [ nonlinear Hawkes process ] [ nonlinear walk ] [ Non-Local Modules ] [ non-minimax optimization ] [ nonnegative PCA ] [ nonseparable Hailtonian system ] [ non-smooth models ] [ non-stationary stochastic processes ] [ no-regret learning ] [ normalized maximum likelihood ] [ normalize layer ] [ normalizers ] [ Normalizing Flow ] [ normalizing flows ] [ Normalizing flows ] [ Normalizing Flows ] [ normative models ] [ novelty-detection ] [ ntk ] [ number of linear regions ] [ numerical errors ] [ numerical linear algebra ] [ object-centric representations ] [ Object detection ] [ Object Detection ] [ object-keypoint representations ] [ ObjectNet ] [ Object Permanence ] [ Observational Imitation ] [ ODE ] [ offline ] [ offline/batch reinforcement learning ] [ off-line reinforcement learning ] [ offline reinforcement learning ] [ Offline Reinforcement Learning ] [ offline RL ] [ off-policy evaluation ] [ Off Policy Evaluation ] [ Off-policy policy evaluation ] [ Off-Policy Reinforcement Learning ] [ off-policy RL ] [ one-class-classification ] [ one-to-many mapping ] [ Open-domain ] [ open domain complex question answering ] [ open source ] [ Optimal Control Theory ] [ optimal convergence ] [ optimal power flow ] [ Optimal Transport ] [ optimal transport maps ] [ Optimisation for Deep Learning ] [ optimism ] [ Optimistic Gradient Descent Ascent ] [ Optimistic Mirror Decent ] [ Optimistic Multiplicative Weights Update ] [ Optimization ] [ order learning ] [ ordinary differential equation ] [ orthogonal ] [ orthogonal layers ] [ orthogonal machine learning ] [ Orthogonal Polynomials ] [ Oscillators ] [ outlier detection ] [ outlier-detection ] [ Outlier detection ] [ out-of-distribution ] [ Out-of-distribution detection in deep learning ] [ out-of-distribution generalization ] [ Out-of-domain ] [ over-fitting ] [ Overfitting ] [ overparameterisation ] [ over-parameterization ] [ Over-parameterization ] [ Overparameterization ] [ overparameterized neural networks ] [ Over-smoothing ] [ Oversmoothing ] [ over-squashing ] [ PAC Bayes ] [ padding ] [ parallel Monte Carlo Tree Search (MCTS) ] [ parallel tempering ] [ Parameter-Reduced MLR ] [ part-based ] [ Partial Amortization ] [ Partial differential equation ] [ partial differential equations ] [ partially observed environments ] [ particle inference ] [ pca ] [ pde ] [ pdes ] [ PDEs ] [ performer ] [ persistence diagrams ] [ personalized learning ] [ perturbation sets ] [ Peter-Weyl Theorem ] [ phase retrieval ] [ Physical parameter estimation ] [ physical reasoning ] [ physical scene understanding ] [ Physical Simulation ] [ physical symbol grounding ] [ physics ] [ physics-guided deep learning ] [ piecewise linear function ] [ pipeline toolkit ] [ plan-based reward shaping ] [ Planning ] [ Poincaré Ball Model ] [ Point cloud ] [ Point clouds ] [ point processes ] [ pointwise mutual information ] [ poisoning ] [ poisoning attack ] [ poisson matrix factorization ] [ policy learning ] [ Policy Optimization ] [ polynomial time ] [ Pose Estimation ] [ Position Embedding ] [ Position Encoding ] [ post-hoc calibration ] [ Post-Hoc Correction ] [ Post Training Quantization ] [ power grid management ] [ Predictive Modeling ] [ predictive uncertainty ] [ Predictive Uncertainty Estimation ] [ pretrained language model ] [ pretrained language model. ] [ pre-trained language model fine-tuning ] [ Pretrained Language Models ] [ Pretrained Text Encoders ] [ pre-training ] [ Pre-training ] [ Primitive Discovery ] [ principal components analysis ] [ Privacy ] [ privacy leakage from gradients ] [ privacy preserving machine learning ] [ Privacy-utility tradeoff ] [ probabelistic models ] [ probabilistic generative models ] [ probabilistic inference ] [ probabilistic matrix factorization ] [ Probabilistic Methods ] [ probabilistic multivariate forecasting ] [ probabilistic numerics ] [ probabilistic programs ] [ probably approximated correct guarantee ] [ Probe ] [ probing ] [ procedural generation ] [ procedural knowledge ] [ product of experts ] [ Product Quantization ] [ Program obfuscation ] [ Program Synthesis ] [ Proper Scoring Rules ] [ protein ] [ prototype propagation ] [ Provable Robustness ] [ provable sample efficiency ] [ proximal gradient descent-ascent ] [ proxy ] [ Pruning ] [ Pruning at initialization ] [ pseudo-labeling ] [ Pseudo-Labeling ] [ QA ] [ Q-learning ] [ Quantization ] [ quantum machine learning ] [ quantum mechanics ] [ Quantum Mechanics ] [ Question Answering ] [ random ] [ Random Feature ] [ Random Features ] [ Randomized Algorithms ] [ Random Matrix Theory ] [ Random Weights Neural Networks ] [ rank-collapse ] [ rank-constrained convex optimization ] [ rao ] [ rao-blackwell ] [ Rate-distortion optimization ] [ raven's progressive matrices ] [ real time recurrent learning ] [ real-world ] [ Real-world image denoising ] [ reasoning paths ] [ recommendation systems ] [ recommender system ] [ Recommender Systems ] [ recovery likelihood ] [ rectified linear unit ] [ Recurrent Generative Model ] [ Recurrent Neural Network ] [ Recurrent neural networks ] [ Recurrent Neural Networks ] [ recursive dense retrieval ] [ reformer ] [ regime agnostic methods ] [ Regression ] [ Regression without correspondence ] [ regret analysis ] [ regret minimization ] [ Regularization ] [ Regularization by denoising ] [ regularized markov decision processes ] [ Reinforcement ] [ Reinforcement learning ] [ Reinforcement Learning ] [ Reinforcement Learnings ] [ Reinforcement learning theory ] [ relabelling ] [ Relational regularized autoencoder ] [ Relation Extraction ] [ relaxed regularization ] [ relu network ] [ ReLU networks ] [ Rematerialization ] [ Render-and-Compare ] [ Reparameterization ] [ repetitions ] [ replica exchange ] [ representational learning ] [ representation analysis ] [ Representation learning ] [ Representation Learning ] [ representation learning for computer vision ] [ representation learning for robotics ] [ representation of dynamical systems ] [ Representation Theory ] [ reproducibility ] [ reproducible research ] [ Reproducing kernel Hilbert space ] [ resampling ] [ reset-free ] [ residual ] [ ResNets ] [ resource constrained ] [ Restricted Boltzmann Machines ] [ retraining ] [ Retrieval ] [ reverse accuracy ] [ reverse engineering ] [ reward learning ] [ reward randomization ] [ reward shaping ] [ reweighting ] [ Rich observation ] [ rich observations ] [ risk-averse ] [ Risk bound ] [ Risk Estimation ] [ risk sensitive ] [ rl ] [ RMSprop ] [ RNA-protein interaction prediction ] [ RNA structure ] [ RNA structure embedding ] [ RNN ] [ RNNs ] [ robotic manipulation ] [ robust ] [ robust control ] [ robust deep learning ] [ Robust Deep Learning ] [ robust learning ] [ Robust Learning ] [ Robust Machine Learning ] [ Robustness ] [ Robustness certificates ] [ Robust Overfitting ] [ ROC ] [ Role-Based Learning ] [ rooted graphs ] [ Rotation invariance ] [ rtrl ] [ Runtime Systems ] [ Saddle-point Optimization ] [ safe ] [ Safe exploration ] [ safe planning ] [ Saliency ] [ Saliency Guided Data Augmentation ] [ saliency maps ] [ SaliencyMix ] [ sample complexity separation ] [ Sample Efficiency ] [ sample information ] [ sample reweighting ] [ Sampling ] [ sampling algorithms ] [ Scalability ] [ Scale ] [ scale-invariant weights ] [ Scale of initialization ] [ scene decomposition ] [ scene generation ] [ Scene Understanding ] [ Science ] [ science of deep learning ] [ score-based generative models ] [ score matching ] [ score-matching ] [ SDE ] [ Second-order analysis ] [ second-order approximation ] [ second-order optimization ] [ Security ] [ segmented models ] [ selective classification ] [ Self-Imitation ] [ self supervised learning ] [ Self-supervised learning ] [ Self-supervised Learning ] [ Self Supervised Learning ] [ Self-Supervised Learning ] [ self-supervision ] [ self-training ] [ self-training theory ] [ semantic anomaly detection ] [ semantic directions in latent space ] [ semantic graphs ] [ Semantic Image Synthesis ] [ semantic parsing ] [ semantic role labeling ] [ semantic-segmentation ] [ Semantic Segmentation ] [ Semantic Textual Similarity ] [ semi-infinite duality ] [ semi-nonnegative matrix factorization ] [ semiparametric inference ] [ semi-supervised ] [ Semi-supervised Learning ] [ Semi-Supervised Learning ] [ semi-supervised learning theory ] [ Sentence Embeddings ] [ Sentence Representations ] [ Sentiment ] [ separation of variables ] [ Sequence Data ] [ Sequence Modeling ] [ sequence models ] [ Sequence-to-sequence learning ] [ sequence-to-sequence models ] [ sequential data ] [ Sequential probability ratio test ] [ Sequential Representation Learning ] [ set prediction ] [ set transformer ] [ SGD ] [ SGD noise ] [ sgld ] [ Shape ] [ shape bias ] [ Shape Bias ] [ Shape Encoding ] [ shapes ] [ Shapley values ] [ Sharpness Minimization ] [ side channel analysis ] [ Sigma Delta Quantization ] [ sign agnostic learning ] [ signal propagation ] [ signature ] [ sim2real ] [ sim2real transfer ] [ simple ] [ Singularity analysis ] [ singular value decomposition ] [ Sinkhorn algorithm ] [ skeleton-based action recognition ] [ sketch-based modeling ] [ sketches ] [ Skill Discovery ] [ SLAM ] [ sliced fused Gromov Wasserstein ] [ Sliced Wasserstein ] [ Slowdown attacks ] [ slowness ] [ Smooth games ] [ smoothing ] [ SMT Solvers ] [ social perception ] [ Soft Body ] [ soft labels ] [ software ] [ sound classification ] [ sound spatialization ] [ Source Code ] [ sparse Bayesian learning ] [ Sparse Embedding ] [ sparse embeddings ] [ sparse reconstruction ] [ sparse representation ] [ sparse representations ] [ sparse stochastic gates ] [ Sparsity ] [ Sparsity Learning ] [ spatial awareness ] [ spatial bias ] [ spatial uncertainty ] [ spatio-temporal forecasting ] [ spatio-temporal graph ] [ spatio-temporal modeling ] [ spatio-temporal modelling ] [ spatiotemporal prediction ] [ Spatiotemporal Understanding ] [ Spectral Analysis ] [ Spectral Distribution ] [ Spectral Graph Filter ] [ spectral regularization ] [ speech generation ] [ speech-impaired ] [ speech processing ] [ speech recognition. ] [ Speech Recognition ] [ spherical distributions ] [ spiking neural network ] [ spurious correlations ] [ square loss vs cross-entropy ] [ stability theory ] [ State abstraction ] [ state abstractions ] [ state-space models ] [ statistical learning theory ] [ Statistical Learning Theory ] [ statistical physics ] [ Statistical Physics ] [ statistical physics methods ] [ Steerable Kernel ] [ Stepsize optimization ] [ stochastic asymptotics ] [ stochastic control ] [ (stochastic) gradient descent ] [ Stochastic Gradient Descent ] [ stochastic gradient Langevin dynamics ] [ stochastic process ] [ Stochastic Processes ] [ stochastic subgradient method ] [ Storage Capacity ] [ straight-through ] [ straightthrough ] [ strategic behavior ] [ Streaming ASR ] [ structural biology ] [ structural credit assignment ] [ structural inductive bias ] [ Structured Pruning ] [ Structure learning ] [ structure prediction ] [ structures prediction ] [ Style Mixing ] [ Style Transfer ] [ subgraph reasoning. ] [ sublinear ] [ submodular optimization ] [ Subspace clustering ] [ Summarization ] [ summary statistics ] [ superpixel ] [ supervised contrastive learning ] [ Supervised Deep Networks ] [ Supervised Learning ] [ support estimation ] [ surprisal ] [ surrogate models ] [ svd ] [ SVD ] [ Symbolic Methods ] [ symbolic regression ] [ symbolic representations ] [ Symmetry ] [ symplectic networks ] [ Syntax ] [ Synthetic benchmark dataset ] [ synthetic-to-real generalization ] [ Systematic generalisation ] [ Systematicity ] [ System identification ] [ Tabular ] [ tabular data ] [ Tabular Data ] [ targeted attack ] [ Task Embeddings ] [ task generation ] [ task-oriented dialogue ] [ Task-oriented Dialogue System ] [ task reduction ] [ Task Segmentation ] [ Teacher-Student Learning ] [ teacher-student model ] [ temporal context ] [ Temporal knowledge graph ] [ temporal networks ] [ tensor product ] [ Text-based Games ] [ Text Representation ] [ Text Retrieval ] [ Text to speech ] [ Text to speech synthesis ] [ text-to-sql ] [ Texture ] [ Texture Bias ] [ Textworld ] [ Theorem proving ] [ theoretical issues in deep learning ] [ theoretical limits ] [ theoretical study ] [ Theory ] [ Theory of deep learning ] [ theory of mind ] [ Third-Person Imitation ] [ Thompson sampling ] [ time-frequency representations ] [ timescale ] [ timescales ] [ Time Series ] [ Time series forecasting ] [ time series prediction ] [ topic modelling ] [ Topology ] [ training dynamics ] [ Training Method ] [ trajectory ] [ trajectory optimization ] [ trajectory prediction ] [ Transferability ] [ Transfer learning ] [ Transfer Learning ] [ transformation invariance ] [ Transformer ] [ Transformers ] [ traveling salesperson problem ] [ Tree-structured Data ] [ trembl ] [ tropical function ] [ trust region ] [ two-layer neural network ] [ Uncertainty ] [ uncertainty calibration ] [ Uncertainty estimates ] [ Uncertainty estimation ] [ Uncertainty Machine Learning ] [ understanding ] [ understanding CNNs ] [ Understanding Data Augmentation ] [ understanding decision-making ] [ understanding deep learning ] [ Understanding Deep Learning ] [ understanding neural networks ] [ U-Net ] [ unidirectional ] [ uniprot ] [ universal approximation ] [ Universal approximation ] [ Universality ] [ universal representation learning ] [ universal sound separation ] [ unlabeled data ] [ Unlabeled Entity Problem ] [ Unlearnable Examples ] [ unrolled algorithms ] [ Unsupervised denoising ] [ Unsupervised Domain Translation ] [ unsupervised image denoising ] [ Unsupervised learning ] [ Unsupervised Learning ] [ unsupervised learning theory ] [ unsupervised loss ] [ Unsupervised Meta-learning ] [ unsupervised object discovery ] [ Unsupervised reinforcement learning ] [ unsupervised skill discovery ] [ unsupervised stabilization ] [ Upper Confidence bound applied to Trees (UCT) ] [ Usable Information ] [ VAE ] [ Value factorization ] [ value learning ] [ vanishing gradient problem ] [ variable binding ] [ variable convergence ] [ Variable Embeddings ] [ Variance Networks ] [ Variational Auto-encoder ] [ Variational autoencoders ] [ Variational Autoencoders ] [ Variational inference ] [ variational information bottleneck ] [ Verification ] [ video analysis ] [ Video Classification ] [ Video Compression ] [ video generation ] [ video-grounded dialogues ] [ Video prediction ] [ Video Reasoning ] [ video recognition ] [ Video Recognition ] [ video representation learning ] [ video synthesis ] [ video-text learning ] [ views ] [ virtual environment ] [ vision-and-language-navigation ] [ visual counting ] [ visualization ] [ visual perception ] [ Visual Reasoning ] [ visual reinforcement learning ] [ visual representation learning ] [ visual saliency ] [ vocoder ] [ voice conversion ] [ Volume Analysis ] [ VQA ] [ vulnerability of RL ] [ wanet ] [ warping functions ] [ Wasserstein ] [ wasserstein-2 barycenters ] [ wasserstein-2 distance ] [ Wasserstein distance ] [ waveform generation ] [ weakly-supervised learning ] [ weakly supervised representation learning ] [ Weak supervision ] [ Weak-supervision ] [ webly-supervised learning ] [ weight attack ] [ weight balance ] [ Weight quantization ] [ weight-sharing ] [ wide local minima ] [ Wigner-Eckart Theorem ] [ winning tickets ] [ wireframe model ] [ word-learning ] [ world models ] [ World Models ] [ worst-case generalisation ] [ xai ] [ XAI ] [ zero-order optimization ] [ zero-shot learning ] [ Zero-shot learning ] [ Zero-shot Learning ] [ Zero-shot synthesis ]

924 Results

Poster
Mon 1:00 Isometric Transformation Invariant and Equivariant Graph Convolutional Networks
Masanobu Horie, Naoki Morita, Toshiaki Hishinuma, Yu Ihara, Naoto Mitsume
Poster
Mon 1:00 Randomized Ensembled Double Q-Learning: Learning Fast Without a Model
Xinyue Chen, Che Wang, Zijian Zhou, Keith Ross
Poster
Mon 1:00 Set Prediction without Imposing Structure as Conditional Density Estimation
David W Zhang, Gertjan J Burghouts, Cees G Snoek
Poster
Mon 1:00 Meta-GMVAE: Mixture of Gaussian VAE for Unsupervised Meta-Learning
Dong Bok Lee, Dongchan Min, Seanie Lee, Sung Ju Hwang
Poster
Mon 1:00 Mutual Information State Intrinsic Control
Rui Zhao, Yang Gao, Pieter Abbeel, Volker Tresp, Wei Xu
Poster
Mon 1:00 Scalable Transfer Learning with Expert Models
Joan Puigcerver Puigcerver i Perez, Carlos Riquelme, Basil Mustafa, Cedric Renggli, André Susano Pinto, Sylvain Gelly, Daniel Keysers, Neil Houlsby
Poster
Mon 1:00 Signatory: differentiable computations of the signature and logsignature transforms, on both CPU and GPU
Patrick Kidger, Terry Lyons
Poster
Mon 1:00 Noise against noise: stochastic label noise helps combat inherent label noise
Pengfei Chen, Guangyong Chen, Junjie Ye, jingwei zhao, Pheng-Ann Heng
Poster
Mon 1:00 MetaNorm: Learning to Normalize Few-Shot Batches Across Domains
Yingjun Du, Xiantong Zhen, Ling Shao, Cees G Snoek
Poster
Mon 1:00 Parameter-Based Value Functions
Francesco Faccio, Louis Kirsch, Jürgen Schmidhuber
Poster
Mon 1:00 Deciphering and Optimizing Multi-Task Learning: a Random Matrix Approach
Malik Tiomoko, Hafiz Tiomoko Ali, Romain Couillet
Poster
Mon 1:00 SALD: Sign Agnostic Learning with Derivatives
Matan Atzmon, Yaron Lipman
Poster
Mon 1:00 Neural Jump Ordinary Differential Equations: Consistent Continuous-Time Prediction and Filtering
Calypso Herrera, Florian Krach, Josef Teichmann
Poster
Mon 1:00 WaNet - Imperceptible Warping-based Backdoor Attack
Tuan Anh Nguyen, Anh T Tran
Poster
Mon 1:00 The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods
Louis THIRY, Michael Arbel, Eugene Belilovsky, Edouard Oyallon
Poster
Mon 1:00 Revisiting Locally Supervised Learning: an Alternative to End-to-end Training
Yulin Wang, Zanlin Ni, Shiji Song, Le Yang, Gao Huang
Poster
Mon 1:00 Spatially Structured Recurrent Modules
Nasim Rahaman, Anirudh Goyal, Waleed Gondal, Manuel Wuthrich, Stefan Bauer, Yash Sharma, Yoshua Bengio, Bernhard Schoelkopf
Poster
Mon 1:00 FairFil: Contrastive Neural Debiasing Method for Pretrained Text Encoders
Pengyu Cheng, Weituo Hao, Siyang Yuan, Shijing Si, Lawrence Carin
Poster
Mon 1:00 Temporally-Extended ε-Greedy Exploration
Will Dabney, Georg Ostrovski, Andre Barreto
Poster
Mon 1:00 What Makes Instance Discrimination Good for Transfer Learning?
Nanxuan Zhao, Zhirong Wu, Rynson W Lau, Stephen Lin
Poster
Mon 1:00 Batch Reinforcement Learning Through Continuation Method
Yijie Guo, Shengyu Feng, Nicolas Le Roux, Ed H. Chi, Honglak Lee, Minmin Chen
Poster
Mon 1:00 Interpreting and Boosting Dropout from a Game-Theoretic View
Hao Zhang, Sen Li, YinChao Ma, Mingjie Li, Yichen Xie, Quanshi Zhang
Poster
Mon 1:00 Domain Generalization with MixStyle
Kaiyang Zhou, Yongxin Yang, Yu Qiao, Tao Xiang
Poster
Mon 1:00 A Unified Approach to Interpreting and Boosting Adversarial Transferability
Xin Wang, Jie Ren, Shuyun Lin, Xiangming Zhu, Yisen Wang, Quanshi Zhang
Poster
Mon 1:00 Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets
Hayeon Lee, Eunyoung Hyung, Sung Ju Hwang
Poster
Mon 1:00 Wasserstein Embedding for Graph Learning
Soheil Kolouri, Navid Naderializadeh, Gustavo K Rohde, Heiko Hoffmann
Poster
Mon 1:00 Towards Impartial Multi-task Learning
Liyang Liu, Yi Li, Zhanghui Kuang, Jing-Hao Xue, Yimin Chen, Wenming Yang, Qingmin Liao, Wei Zhang
Poster
Mon 1:00 MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space
Tsz Him Cheung, Dit-Yan Yeung
Poster
Mon 1:00 Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch
Aojun Zhou, Yukun Ma, Junnan Zhu, Jianbo Liu, Zhijie Zhang, Kun Yuan, Wenxiu Sun, Hongsheng Li
Poster
Mon 1:00 Trusted Multi-View Classification
Zongbo Han, Changqing Zhang, Huazhu FU, Joey T Zhou
Poster
Mon 1:00 Solving Compositional Reinforcement Learning Problems via Task Reduction
Yunfei Li, Yilin Wu, Huazhe Xu, Xiaolong Wang, Yi Wu
Poster
Mon 1:00 Neural Approximate Sufficient Statistics for Implicit Models
Yanzhi Chen, Dinghuai Zhang, Michael U Gutmann, Aaron Courville, Zhanxing Zhu
Poster
Mon 1:00 Improve Object Detection with Feature-based Knowledge Distillation: Towards Accurate and Efficient Detectors
Linfeng Zhang, Kaisheng Ma
Poster
Mon 1:00 On the Transfer of Disentangled Representations in Realistic Settings
Andrea Dittadi, Frederik Träuble, Francesco Locatello, Manuel Wuthrich, Vaibhav Agrawal, Ole Winther, Stefan Bauer, Bernhard Schoelkopf
Poster
Mon 1:00 Predicting Infectiousness for Proactive Contact Tracing
Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif B Muller, Meng Qu, victor schmidt, Pierre-luc St-charles, hannah alsdurf, Olexa Bilaniuk, david buckeridge, Gaétan Marceau Caron, pierre carrier, Joumana Ghosn, satya gagne, Chris J Pal, Irina Rish, Bernhard Schoelkopf, abhinav sharma, Jian Tang, Andrew Williams
Poster
Mon 1:00 MELR: Meta-Learning via Modeling Episode-Level Relationships for Few-Shot Learning
Nanyi Fei, Zhiwu Lu, Tao Xiang, Songfang Huang
Poster
Mon 1:00 On Learning Universal Representations Across Languages
Xiangpeng Wei, Rongxiang Weng, Yue Hu, Luxi Xing, Heng Yu, Weihua Luo
Poster
Mon 1:00 On InstaHide, Phase Retrieval, and Sparse Matrix Factorization
Sitan Chen, Xiaoxiao Li, Zhao Song, Danyang Zhuo
Poster
Mon 1:00 A Good Image Generator Is What You Need for High-Resolution Video Synthesis
Yu Tian, Jian Ren, Menglei Chai, Kyle Olszewski, Xi Peng, Dimitris Metaxas, Sergey Tulyakov
Poster
Mon 1:00 Exploring Balanced Feature Spaces for Representation Learning
Bingyi Kang, Yu Li, Sain Xie, Zehuan Yuan, Jiashi Feng
Poster
Mon 1:00 Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs
Cheng Wang, Carolin Lawrence, Mathias Niepert
Poster
Mon 1:00 SaliencyMix: A Saliency Guided Data Augmentation Strategy for Better Regularization
A F M Shahab Uddin, Mst. Sirazam Monira, Wheemyung Shin, TaeChoong Chung, Sung-Ho Bae
Poster
Mon 1:00 QPLEX: Duplex Dueling Multi-Agent Q-Learning
Jianhao Wang, Zhizhou Ren, Terry Liu, Yang Yu, Chongjie Zhang
Poster
Mon 1:00 Overfitting for Fun and Profit: Instance-Adaptive Data Compression
Ties van Rozendaal, Iris Huijben, Taco Cohen
Oral
Mon 3:00 Dataset Condensation with Gradient Matching
Bo ZHAO, Konda Reddy Mopuri, Hakan Bilen
Oral
Mon 3:15 Free Lunch for Few-shot Learning: Distribution Calibration
Shuo Yang, Lu Liu, Min Xu
Spotlight
Mon 3:30 Deciphering and Optimizing Multi-Task Learning: a Random Matrix Approach
Malik Tiomoko, Hafiz Tiomoko Ali, Romain Couillet
Spotlight
Mon 3:40 Generalization in data-driven models of primary visual cortex
Konstantin-Klemens Lurz, Mohammad Bashiri, Konstantin Willeke, Akshay Jagadish, Eric Wang, Edgar Walker, Santiago Cadena Cadena, Taliah Muhammad, Erick M Cobos, Andreas Tolias, Alexander S Ecker, Fabian Sinz
Spotlight
Mon 4:30 The Intrinsic Dimension of Images and Its Impact on Learning
Phil Pope, Chen Zhu, Ahmed Abdelkader, Micah Goldblum, Tom Goldstein
Spotlight
Mon 4:40 How Benign is Benign Overfitting ?
Amartya Sanyal, Puneet Dokania, Varun Kanade, Philip Torr
Oral
Mon 5:00 Geometry-aware Instance-reweighted Adversarial Training
Jingfeng Zhang, Jianing ZHU, Gang Niu, Bo Han, Masashi Sugiyama, Mohan Kankanhalli
Spotlight
Mon 5:45 Contrastive Divergence Learning is a Time Reversal Adversarial Game
Omer Yair, Tomer Michaeli
Mon 6:00 WiML@ICLR 2021 Virtual Panel
Invited Talk
Mon 8:00 Moving beyond the fairness rhetoric in machine learning
Timnit Gebru
Poster
Mon 9:00 Selectivity considered harmful: evaluating the causal impact of class selectivity in DNNs
Matthew Leavitt, Ari Morcos
Poster
Mon 9:00 Self-Supervised Policy Adaptation during Deployment
Nicklas Hansen, Rishabh Jangir, Yu Sun, Guillem Alenyà, Pieter Abbeel, Alyosha Efros, Lerrel Pinto, Xiaolong Wang
Poster
Mon 9:00 Learning with AMIGo: Adversarially Motivated Intrinsic Goals
Andres Campero, Roberta Raileanu, Heinrich Kuttler, Joshua B Tenenbaum, Tim Rocktaeschel, Ed Grefenstette
Poster
Mon 9:00 Teaching Temporal Logics to Neural Networks
Christopher Hahn, Frederik Schmitt, Jens Kreber, Markus Rabe, Bernd Finkbeiner
Poster
Mon 9:00 Reset-Free Lifelong Learning with Skill-Space Planning
Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch
Poster
Mon 9:00 Disentangling 3D Prototypical Networks for Few-Shot Concept Learning
Mihir Prabhudesai, Shamit Lal, Darshan Patil, Hsiao-Yu Tung, Adam Harley, Katerina Fragkiadaki
Poster
Mon 9:00 LambdaNetworks: Modeling long-range Interactions without Attention
Irwan Bello
Poster
Mon 9:00 Gradient Projection Memory for Continual Learning
Gobinda Saha, Isha Garg, Kaushik Roy
Poster
Mon 9:00 Conditional Negative Sampling for Contrastive Learning of Visual Representations
Mike Wu, Milan Mosse, Chengxu Zhuang, Daniel Yamins, Noah Goodman
Poster
Mon 9:00 X2T: Training an X-to-Text Typing Interface with Online Learning from User Feedback
Jensen Gao, Siddharth Reddy, Glen Berseth, Nick Hardy, Nikhilesh Natraj, Karunesh Ganguly, Anca Dragan, Sergey Levine
Poster
Mon 9:00 Rapid Task-Solving in Novel Environments
Samuel Ritter, Ryan Faulkner, Laurent Sartran, Adam Santoro, Matthew Botvinick, David Raposo
Poster
Mon 9:00 On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines
Marius Mosbach, Maksym Andriushchenko, Dietrich Klakow
Mon 9:00 Philosophy and AGI (#1)
Poster
Mon 9:00 Extracting Strong Policies for Robotics Tasks from Zero-Order Trajectory Optimizers
Cristina Pinneri, Shambhuraj Sawant, Sebastian Blaes, Georg Martius
Poster
Mon 9:00 Learning Structural Edits via Incremental Tree Transformations
Ziyu Yao, Frank F Xu, Pengcheng Yin, Huan Sun, Graham Neubig
Poster
Mon 9:00 Primal Wasserstein Imitation Learning
Robert Dadashi, Hussenot Hussenot-Desenonges, Matthieu Geist, Olivier Pietquin
Poster
Mon 9:00 Representation learning for improved interpretability and classification accuracy of clinical factors from EEG
Garrett Honke, Irina Higgins, Nina Thigpen, Vladimir Miskovic, Katie Link, Sunny Duan, Pramod Gupta, Julia Klawohn, Greg Hajcak
Poster
Mon 9:00 Multi-Level Local SGD: Distributed SGD for Heterogeneous Hierarchical Networks
Timothy Castiglia, Anirban Das, Stacy Patterson
Poster
Mon 9:00 Share or Not? Learning to Schedule Language-Specific Capacity for Multilingual Translation
Biao Zhang, Ankur Bapna, Rico Sennrich, Orhan Firat
Poster
Mon 9:00 Trajectory Prediction using Equivariant Continuous Convolution
Robin Walters, Jinxi Li, Rose Yu
Poster
Mon 9:00 Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels
Denis Yarats, Ilya Kostrikov, Rob Fergus
Poster
Mon 9:00 On the role of planning in model-based deep reinforcement learning
Jessica Hamrick, Abram Friesen, Feryal Behbahani, Arthur Guez, Fabio Viola, Sims Witherspoon, Thomas Anthony, Lars Buesing, Petar Veličković, Theo Weber
Poster
Mon 9:00 Fast convergence of stochastic subgradient method under interpolation
Huang Fang, Zhenan Fan, Michael Friedlander
Poster
Mon 9:00 What Can You Learn From Your Muscles? Learning Visual Representation from Human Interactions
Kiana Ehsani, Daniel Gordon, Thomas H Nguyen, Roozbeh Mottaghi, Ali Farhadi
Poster
Mon 9:00 Unsupervised Meta-Learning through Latent-Space Interpolation in Generative Models
Siavash Khodadadeh, Sharare Zehtabian, Saeed Vahidian, Weijia Wang, Bill Lin, Ladislau Boloni
Poster
Mon 9:00 The role of Disentanglement in Generalisation
Milton Montero, Casimir JH Ludwig, Rui Ponte Costa, Gaurav Malhotra, Jeffrey Bowers
Poster
Mon 9:00 Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections
Csaba Toth, Patric Bonnier, Harald Oberhauser
Poster
Mon 9:00 Shapley Explanation Networks
Rui Wang, Xiaoqian Wang, David Inouye
Poster
Mon 9:00 Into the Wild with AudioScope: Unsupervised Audio-Visual Separation of On-Screen Sounds
Efthymios Tzinis, Scott Wisdom, Aren Jansen, Shawn Hershey, Tal Remez, Dan Ellis, John Hershey
Poster
Mon 9:00 InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective
Boxin Wang, Shuohang Wang, Yu Cheng, Zhe Gan, Ruoxi Jia, Bo Li, Jingjing Liu
Poster
Mon 9:00 Learning Hyperbolic Representations of Topological Features
Panagiotis Kyriakis, Iordanis Fostiropoulos, Paul Bogdan
Poster
Mon 9:00 Learning from others' mistakes: Avoiding dataset biases without modeling them
Victor Sanh, Thomas Wolf, Yonatan Belinkov, Alexander M Rush
Poster
Mon 9:00 NeMo: Neural Mesh Models of Contrastive Features for Robust 3D Pose Estimation
Angtian Wang, Adam Kortylewski, Alan Yuille
Poster
Mon 9:00 Planning from Pixels using Inverse Dynamics Models
Keiran Paster, Sheila McIlraith, Jimmy Ba
Poster
Mon 9:00 Learning-based Support Estimation in Sublinear Time
talyaa01 Eden, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner
Poster
Mon 9:00 On Statistical Bias In Active Learning: How and When to Fix It
Sebastian Farquhar, Yarin Gal, Tom Rainforth
Poster
Mon 9:00 Symmetry-Aware Actor-Critic for 3D Molecular Design
Gregor Simm, Robert Pinsler, Gábor Csányi, José Miguel Hernández Lobato
Poster
Mon 9:00 Single-Photon Image Classification
Thomas Fischbacher, Luciano Sbaiz
Poster
Mon 9:00 Plan-Based Relaxed Reward Shaping for Goal-Directed Tasks
Ingmar Schubert, Oz Oguz, Marc Toussaint
Poster
Mon 9:00 On the Universality of Rotation Equivariant Point Cloud Networks
Nadav Dym, Haggai Maron
Poster
Mon 9:00 The Traveling Observer Model: Multi-task Learning Through Spatial Variable Embeddings
Elliot Meyerson, Risto Miikkulainen
Poster
Mon 9:00 Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction
Wei Deng, Qi Feng, Georgios Karagiannis, Guang Lin, Faming Liang
Poster
Mon 9:00 Grounding Physical Concepts of Objects and Events Through Dynamic Visual Reasoning
Zhenfang Chen, Jiayuan Mao, Jiajun Wu, Kwan-Yee K Wong, Joshua B Tenenbaum, Chuang Gan
Poster
Mon 9:00 Understanding the failure modes of out-of-distribution generalization
Vaishnavh Nagarajan, Anders J Andreassen, Behnam Neyshabur
Poster
Mon 9:00 Structured Prediction as Translation between Augmented Natural Languages
Giovanni Paolini, Ben Athiwaratkun, Jason Krone, Jie Ma, Alessandro Achille, RISHITA ANUBHAI, Cicero Nogueira dos Santos, Bing Xiang, Stefano Soatto
Poster
Mon 9:00 Effective Distributed Learning with Random Features: Improved Bounds and Algorithms
Yong Liu, Jiankun Liu, Shuqiang Wang
Poster
Mon 9:00 Parameter Efficient Multimodal Transformers for Video Representation Learning
Sangho Lee, Youngjae Yu, Gunhee Kim, Thomas Breuel, Jan Kautz, Yale Song
Poster
Mon 9:00 Adaptive Federated Optimization
Sashank Reddi, Zachary Charles, Manzil Zaheer, Zachary Garrett, Keith Rush, Jakub Konečný, Sanjiv Kumar, Brendan McMahan
Poster
Mon 9:00 Intrinsic-Extrinsic Convolution and Pooling for Learning on 3D Protein Structures
Pedro Hermosilla Casajus, Marco Schäfer, Matej Lang, Gloria Fackelmann, Pere-Pau Vázquez, Barbora Kozlikova, Michael Krone, Tobias Ritschel, Timo Ropinski
Poster
Mon 9:00 Multi-Time Attention Networks for Irregularly Sampled Time Series
Satya Narayan Shukla, Benjamin M Marlin
Poster
Mon 9:00 Shape-Texture Debiased Neural Network Training
Yinigwei Li, Qihang Yu, Mingxing Tan, Jieru Mei, Peng Tang, Wei Shen, Alan Yuille, Cihang Xie
Poster
Mon 9:00 Learning Invariant Representations for Reinforcement Learning without Reconstruction
Amy Zhang, Rowan T McAllister, Roberto Calandra, Yarin Gal, Sergey Levine
Poster
Mon 9:00 Zero-Cost Proxies for Lightweight NAS
Mohamed Abdelfattah, Abhinav Mehrotra, Łukasz Dudziak, Nic Lane
Poster
Mon 9:00 Learning "What-if" Explanations for Sequential Decision-Making
Ioana Bica, Dan Jarrett, Alihan Hüyük, Mihaela van der Schaar
Poster
Mon 9:00 Learning explanations that are hard to vary
Giambattista Parascandolo, Alexander Neitz, Antonio Orvieto, Luigi Gresele, Bernhard Schoelkopf
Poster
Mon 9:00 Training GANs with Stronger Augmentations via Contrastive Discriminator
Jongheon Jeong, Jinwoo Shin
Poster
Mon 9:00 Language-Agnostic Representation Learning of Source Code from Structure and Context
Daniel Zügner, Tobias Kirschstein, Michele Catasta, Jure Leskovec, Stephan Günnemann
Poster
Mon 9:00 Rethinking Embedding Coupling in Pre-trained Language Models
Hyung Won Chung, Thibault Fevry, Henry Tsai, Melvin Johnson, Sebastian Ruder
Poster
Mon 9:00 Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers
Ben Eysenbach, Shreyas Chaudhari, Swapnil Asawa, Sergey Levine, Ruslan Salakhutdinov
Poster
Mon 9:00 What Should Not Be Contrastive in Contrastive Learning
Tete Xiao, Xiaolong Wang, Alyosha Efros, trevor darrell
Poster
Mon 9:00 The Risks of Invariant Risk Minimization
Elan Rosenfeld, Pradeep K Ravikumar, Andrej Risteski
Poster
Mon 9:00 On the Impossibility of Global Convergence in Multi-Loss Optimization
Alistair Letcher
Oral
Mon 11:00 Federated Learning Based on Dynamic Regularization
Durmus Alp Emre Acar, Yue Zhao, Ramon Matas, Matthew Mattina, Paul Whatmough, Venkatesh Saligrama
Oral
Mon 11:15 Gradient Projection Memory for Continual Learning
Gobinda Saha, Isha Garg, Kaushik Roy
Oral
Mon 11:30 Growing Efficient Deep Networks by Structured Continuous Sparsification
Xin Yuan, Pedro Savarese, Michael Maire
Spotlight
Mon 11:45 Geometry-Aware Gradient Algorithms for Neural Architecture Search
Liam Li, Misha Khodak, Nina Balcan, Ameet Talwalkar
Spotlight
Mon 12:05 Generalization bounds via distillation
Daniel Hsu, Ziwei Ji, Matus Telgarsky, Lan Wang
Spotlight
Mon 12:15 On the Theory of Implicit Deep Learning: Global Convergence with Implicit Layers
Kenji Kawaguchi
Spotlight
Mon 12:25 Sharpness-aware Minimization for Efficiently Improving Generalization
Pierre Foret, Ariel Kleiner, Hossein Mobahi, Behnam Neyshabur
Spotlight
Mon 12:45 On Statistical Bias In Active Learning: How and When to Fix It
Sebastian Farquhar, Yarin Gal, Tom Rainforth
Spotlight
Mon 12:55 Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images
Rewon Child
Spotlight
Mon 13:40 Gradient Vaccine: Investigating and Improving Multi-task Optimization in Massively Multilingual Models
Zirui Wang, Yulia Tsvetkov, Orhan Firat, Yuan Cao
Spotlight
Mon 13:50 Watch-And-Help: A Challenge for Social Perception and Human-AI Collaboration
Xavier Puig, Tianmin Shu, Shuang Li, Zilin Wang, Andrew Liao, Joshua B Tenenbaum, Sanja Fidler, Antonio Torralba
Spotlight
Mon 14:00 Predicting Infectiousness for Proactive Contact Tracing
Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif B Muller, Meng Qu, victor schmidt, Pierre-luc St-charles, hannah alsdurf, Olexa Bilaniuk, david buckeridge, Gaétan Marceau Caron, pierre carrier, Joumana Ghosn, satya gagne, Chris J Pal, Irina Rish, Bernhard Schoelkopf, abhinav sharma, Jian Tang, Andrew Williams
Invited Talk
Mon 16:00 Commonsense AI: Myth and Truth
Yejin Choi
Poster
Mon 17:00 Regularization Matters in Policy Optimization - An Empirical Study on Continuous Control
Zhuang Liu, Xuanlin Li, Bingyi Kang, trevor darrell
Poster
Mon 17:00 Why resampling outperforms reweighting for correcting sampling bias with stochastic gradients
Jing An, Lexing Ying, Yuhua Zhu
Poster
Mon 17:00 Tilted Empirical Risk Minimization
Tian Li, Ahmad Beirami, Maziar Sanjabi, Virginia Smith
Poster
Mon 17:00 On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning
Ren Wang, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Lily Weng, Chuang Gan, Meng Wang
Poster
Mon 17:00 DeLighT: Deep and Light-weight Transformer
Sachin Mehta, Marjan Ghazvininejad, Srini Iyer, Luke Zettlemoyer, Hannaneh Hajishirzi
Poster
Mon 17:00 MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training
Beidi Chen, Zichang Liu, Binghui Peng, Zhaozhuo Xu, Jonathan L Li, Tri Dao, Zhao Song, Anshumali Shrivastava, Christopher Re
Poster
Mon 17:00 What are the Statistical Limits of Offline RL with Linear Function Approximation?
Ruosong Wang, Dean Foster, Sham M Kakade
Poster
Mon 17:00 The Deep Bootstrap Framework: Good Online Learners are Good Offline Generalizers
Preetum Nakkiran, Behnam Neyshabur, Hanie Sedghi
Poster
Mon 17:00 Robust Curriculum Learning: from clean label detection to noisy label self-correction
Tianyi Zhou, Shengjie Wang, Jeff Bilmes
Poster
Mon 17:00 MixKD: Towards Efficient Distillation of Large-scale Language Models
Kevin Liang, Weituo Hao, Dinghan Shen, Yufan Zhou, Weizhu Chen, Changyou Chen, Lawrence Carin
Poster
Mon 17:00 Online Adversarial Purification based on Self-supervised Learning
Changhao Shi, Chester Holtz, Gal Mishne
Poster
Mon 17:00 Learning Energy-Based Models by Diffusion Recovery Likelihood
Ruiqi Gao, Yang Song, Ben Poole, Yingnian Wu, Durk Kingma
Poster
Mon 17:00 PlasticineLab: A Soft-Body Manipulation Benchmark with Differentiable Physics
Zhiao Huang, Yuanming Hu, Tao Du, Siyuan Zhou, Hao Su, Joshua B Tenenbaum, Chuang Gan
Poster
Mon 17:00 On Dyadic Fairness: Exploring and Mitigating Bias in Graph Connections
Peizhao Li, Yifei Wang, Han Zhao, Pengyu Hong, Hongfu Liu
Poster
Mon 17:00 VA-RED$^2$: Video Adaptive Redundancy Reduction
Bowen Pan, Rameswar Panda, Camilo L Fosco, Chung-Ching Lin, Alex J Andonian, Yue Meng, Kate Saenko, Aude Oliva, Rogerio Feris
Poster
Mon 17:00 One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks
Atish Agarwala, Abhimanyu Das, Brendan Juba, Rina Panigrahy, Vatsal Sharan, Xin Wang, Qiuyi Zhang
Poster
Mon 17:00 Unlearnable Examples: Making Personal Data Unexploitable
Hanxun Huang, Daniel Ma, Sarah Erfani, James Bailey, Yisen Wang
Poster
Mon 17:00 Remembering for the Right Reasons: Explanations Reduce Catastrophic Forgetting
Sayna Ebrahimi, Suzanne Petryk, Akash Gokul, William Gan, Joseph E Gonzalez, Marcus Rohrbach, trevor darrell
Poster
Mon 17:00 MALI: A memory efficient and reverse accurate integrator for Neural ODEs
Juntang Zhuang, Nicha C Dvornek, sekhar tatikonda, James s Duncan
Poster
Mon 17:00 The Role of Momentum Parameters in the Optimal Convergence of Adaptive Polyak's Heavy-ball Methods
Wei Tao, sheng long, Gaowei Wu, Qing Tao
Poster
Mon 17:00 Meta-Learning with Neural Tangent Kernels
Yufan Zhou, Zhenyi Wang, Jiayi Xian, Changyou Chen, Jinhui Xu
Poster
Mon 17:00 Robust Reinforcement Learning on State Observations with Learned Optimal Adversary
Huan Zhang, Hongge Chen, Duane S Boning, Cho-Jui Hsieh
Poster
Mon 17:00 Optimizing Memory Placement using Evolutionary Graph Reinforcement Learning
Shauharda Khadka, Estelle Aflalo, Mattias Marder, Avrech Ben-David, Santiago Miret, Shie Mannor, Tamir Hazan, Hanlin Tang, Somdeb Majumdar
Poster
Mon 17:00 Zero-shot Synthesis with Group-Supervised Learning
Yunhao Ge, Sami Abu-El-Haija, Gan Xin, Laurent Itti
Poster
Mon 17:00 Federated Learning Based on Dynamic Regularization
Durmus Alp Emre Acar, Yue Zhao, Ramon Matas, Matthew Mattina, Paul Whatmough, Venkatesh Saligrama
Poster
Mon 17:00 The Intrinsic Dimension of Images and Its Impact on Learning
Phil Pope, Chen Zhu, Ahmed Abdelkader, Micah Goldblum, Tom Goldstein
Poster
Mon 17:00 PseudoSeg: Designing Pseudo Labels for Semantic Segmentation
Yuliang Zou, Zizhao Zhang, Han Zhang, Chun-Liang Li, Xiao Bian, Jia-Bin Huang, Tomas Pfister
Poster
Mon 17:00 Learning a Latent Simplex in Input Sparsity Time
Ainesh Bakshi, Chiranjib Bhattacharyya, Ravi Kannan, David Woodruff, Samson Zhou
Poster
Mon 17:00 Personalized Federated Learning with First Order Model Optimization
Michael Zhang, Karan Sapra, Sanja Fidler, Serena Yeung, Jose M. Alvarez
Poster
Mon 17:00 Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning
Tianlong Chen, Zhenyu Zhang, Sijia Liu, Shiyu Chang, Zhangyang Wang
Poster
Mon 17:00 Latent Skill Planning for Exploration and Transfer
Kevin Xie, Homanga Bharadhwaj, Danijar Hafner, Animesh Garg, Florian Shkurti
Poster
Mon 17:00 Benefit of deep learning with non-convex noisy gradient descent: Provable excess risk bound and superiority to kernel methods
Taiji Suzuki, Akiyama Shunta
Poster
Mon 17:00 SOLAR: Sparse Orthogonal Learned and Random Embeddings
Tharun Medini Medini, Beidi Chen, Anshumali Shrivastava
Poster
Mon 17:00 Contextual Transformation Networks for Online Continual Learning
Quang Pham, Chenghao Liu, Doyen Sahoo, Steven HOI
Poster
Mon 17:00 SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness
Mikhail Yurochkin, Yuekai Sun
Poster
Mon 17:00 Robust and Generalizable Visual Representation Learning via Random Convolutions
Zhenlin Xu, Deyi Liu, Junlin Yang, Colin Raffel, Marc Niethammer
Poster
Mon 17:00 Representation Learning for Sequence Data with Deep Autoencoding Predictive Components
Junwen Bai, Weiran Wang, Yingbo Zhou, Caiming Xiong
Poster
Mon 17:00 Model Patching: Closing the Subgroup Performance Gap with Data Augmentation
Karan Goel, Albert Gu, Yixuan Li, Christopher Re
Poster
Mon 17:00 Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images
Rewon Child
Poster
Mon 17:00 Deep Partition Aggregation: Provable Defenses against General Poisoning Attacks
Alexander Levine, Soheil Feizi
Poster
Mon 17:00 On the geometry of generalization and memorization in deep neural networks
Cory Stephenson, Suchi Padhy, Abhinav Ganesh, Yue Hui, Hanlin Tang, SueYeon Chung
Poster
Mon 17:00 Semi-supervised Keypoint Localization
Olga Moskvyak, Frederic Maire, Feras Dayoub, Mahsa Baktashmotlagh
Poster
Mon 17:00 Parrot: Data-Driven Behavioral Priors for Reinforcement Learning
Avi Singh, Huihan Liu, Gaoyue Zhou, Albert Yu, Nicholas Rhinehart, Sergey Levine
Poster
Mon 17:00 UPDeT: Universal Multi-agent RL via Policy Decoupling with Transformers
Siyi Hu, Fengda Zhu, Xiaojun Chang, Xiaodan Liang
Poster
Mon 17:00 Learning A Minimax Optimizer: A Pilot Study
Jiayi Shen, Xiaohan Chen, Howard Heaton, Tianlong Chen, Jialin Liu, Wotao Yin, Zhangyang Wang
Poster
Mon 17:00 Self-training For Few-shot Transfer Across Extreme Task Differences
Cheng Phoo, Bharath Hariharan
Poster
Mon 17:00 Variational Intrinsic Control Revisited
Taehwan Kwon
Poster
Mon 17:00 When Optimizing $f$-Divergence is Robust with Label Noise
Jiaheng Wei, Yang Liu
Poster
Mon 17:00 MoPro: Webly Supervised Learning with Momentum Prototypes
Junnan Li, Caiming Xiong, Steven Hoi
Poster
Mon 17:00 Random Feature Attention
Hao Peng, Nikolaos Pappas, Dani Yogatama, Roy Schwartz, Noah Smith, Lingpeng Kong
Poster
Mon 17:00 Optimal Regularization can Mitigate Double Descent
Preetum Nakkiran, Prayaag Venkat, Sham M Kakade, Tengyu Ma
Poster
Mon 17:00 Undistillable: Making A Nasty Teacher That CANNOT teach students
Haoyu Ma, Tianlong Chen, Ting-Kuei Hu, Chenyu You, Xiaohui Xie, Zhangyang Wang
Poster
Mon 17:00 Explaining the Efficacy of Counterfactually Augmented Data
Divyansh Kaushik, Amrith Setlur, Eduard H Hovy, Zachary Lipton
Poster
Mon 17:00 Incorporating Symmetry into Deep Dynamics Models for Improved Generalization
Rui Wang, Robin Walters, Rose Yu
Poster
Mon 17:00 Regularized Inverse Reinforcement Learning
Wonseok Jeon, Chen-Yang Su, Paul Barde, Thang Doan, Derek Nowrouzezahrai, Joelle Pineau
Oral
Mon 19:00 SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments
Glen Berseth, Daniel Geng, Coline M Devin, Nicholas Rhinehart, Chelsea Finn, Dinesh Jayaraman, Sergey Levine
Oral
Mon 19:15 Contrastive Explanations for Reinforcement Learning via Embedded Self Predictions
Zhengxian Lin, Kin-Ho Lam, Alan Fern
Oral
Mon 19:30 Parrot: Data-Driven Behavioral Priors for Reinforcement Learning
Avi Singh, Huihan Liu, Gaoyue Zhou, Albert Yu, Nicholas Rhinehart, Sergey Levine
Spotlight
Mon 19:45 Structured Prediction as Translation between Augmented Natural Languages
Giovanni Paolini, Ben Athiwaratkun, Jason Krone, Jie Ma, Alessandro Achille, RISHITA ANUBHAI, Cicero Nogueira dos Santos, Bing Xiang, Stefano Soatto
Spotlight
Mon 19:55 Mathematical Reasoning via Self-supervised Skip-tree Training
Markus Rabe, Dennis Lee, Kshitij Bansal, Christian Szegedy
Spotlight
Mon 20:18 Improving Adversarial Robustness via Channel-wise Activation Suppressing
Yang Bai, Yuyuan Zeng, Yong Jiang, Shu-Tao Xia, Daniel Ma, Yisen Wang
Spotlight
Mon 20:38 Information Laundering for Model Privacy
Xinran Wang, Yu Xiang, Jun Gao, Jie Ding
Spotlight
Mon 20:48 Dataset Inference: Ownership Resolution in Machine Learning
Pratyush Maini, Mohammad Yaghini, Nicolas Papernot
Oral
Mon 21:21 How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks
Keyulu Xu, Mozhi Zhang, Jingling Li, Simon Du, Ken-Ichi Kawarabayashi, Stefanie Jegelka
Spotlight
Mon 21:46 The Traveling Observer Model: Multi-task Learning Through Spatial Variable Embeddings
Elliot Meyerson, Risto Miikkulainen
Spotlight
Mon 21:56 Meta-GMVAE: Mixture of Gaussian VAE for Unsupervised Meta-Learning
Dong Bok Lee, Dongchan Min, Seanie Lee, Sung Ju Hwang
Invited Talk
Tue 0:00 Geometric Deep Learning: the Erlangen Programme of ML
Michael Bronstein
Poster
Tue 1:00 Learning Subgoal Representations with Slow Dynamics
Siyuan Li, Lulu Zheng, Jianhao Wang, Chongjie Zhang
Poster
Tue 1:00 Computational Separation Between Convolutional and Fully-Connected Networks
Eran Malach, Shai Shalev-Shwartz
Poster
Tue 1:00 Learning the Pareto Front with Hypernetworks
Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik
Poster
Tue 1:00 Generalized Multimodal ELBO
Thomas Sutter, Imant Daunhawer, Julia E Vogt
Poster
Tue 1:00 Large-width functional asymptotics for deep Gaussian neural networks
Daniele Bracale, Stefano Favaro, Sandra Fortini, Stefano Peluchetti
Poster
Tue 1:00 Auxiliary Learning by Implicit Differentiation
Aviv Navon, Idan Achituve, Haggai Maron, Gal Chechik, Ethan Fetaya
Poster
Tue 1:00 Calibration tests beyond classification
David Widmann, Fredrik Lindsten, Dave Zachariah
Poster
Tue 1:00 Contemplating Real-World Object Classification
Ali Borji
Poster
Tue 1:00 Intraclass clustering: an implicit learning ability that regularizes DNNs
Simon Carbonnelle, Christophe De Vleeschouwer
Poster
Tue 1:00 Policy-Driven Attack: Learning to Query for Hard-label Black-box Adversarial Examples
Ziang Yan, Yiwen Guo, Jian Liang, Changshui Zhang
Poster
Tue 1:00 Learning Accurate Entropy Model with Global Reference for Image Compression
Yichen Qian, Zhiyu Tan, Xiuyu Sun, Ming Lin, Dongyang Li, Zhenhong Sun, Li Hao, Rong Jin
Poster
Tue 1:00 Effective Abstract Reasoning with Dual-Contrast Network
Tao Zhuo, Mohan Kankanhalli
Poster
Tue 1:00 A Trainable Optimal Transport Embedding for Feature Aggregation and its Relationship to Attention
Grégoire Mialon, Dexiong Chen, Alexandre d'Aspremont, Julien Mairal
Poster
Tue 1:00 Improving Transformation Invariance in Contrastive Representation Learning
Adam Foster, Rattana Pukdee, Tom Rainforth
Poster
Tue 1:00 MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering
Tsung Wei Tsai, Chongxuan Li, Jun Zhu
Poster
Tue 1:00 Model-based micro-data reinforcement learning: what are the crucial model properties and which model to choose?
Balázs Kégl, Gabriel Hurtado, Albert Thomas
Poster
Tue 1:00 Conformation-Guided Molecular Representation with Hamiltonian Neural Networks
Ziyao Li, Shuwen Yang, Guojie Song, Lingsheng Cai
Poster
Tue 1:00 Lossless Compression of Structured Convolutional Models via Lifting
Gustav Sourek, Filip Zelezny, Ondrej Kuzelka
Poster
Tue 1:00 Winning the L2RPN Challenge: Power Grid Management via Semi-Markov Afterstate Actor-Critic
Deunsol Yoon, Sunghoon Hong, Byung-Jun Lee, Kee-Eung Kim
Poster
Tue 1:00 Learning Incompressible Fluid Dynamics from Scratch - Towards Fast, Differentiable Fluid Models that Generalize
Nils Wandel, Michael Weinmann, Reinhard Klein
Poster
Tue 1:00 Scaling the Convex Barrier with Active Sets
Alessandro De Palma, Harkirat Singh Behl, Rudy R Bunel, Philip Torr, M. Pawan Kumar
Poster
Tue 1:00 Activation-level uncertainty in deep neural networks
Pablo Morales-Alvarez, Daniel Hernández-Lobato, Rafael Molina, José Miguel Hernández Lobato
Poster
Tue 1:00 Generalization in data-driven models of primary visual cortex
Konstantin-Klemens Lurz, Mohammad Bashiri, Konstantin Willeke, Akshay Jagadish, Eric Wang, Edgar Walker, Santiago Cadena Cadena, Taliah Muhammad, Erick M Cobos, Andreas Tolias, Alexander S Ecker, Fabian Sinz
Poster
Tue 1:00 Prototypical Contrastive Learning of Unsupervised Representations
Junnan Li, Pan Zhou, Caiming Xiong, Steven Hoi
Poster
Tue 1:00 Learning Better Structured Representations Using Low-rank Adaptive Label Smoothing
Asish Ghoshal, Xilun Chen, Sonal Gupta, Luke Zettlemoyer, Yashar Mehdad
Poster
Tue 1:00 Group Equivariant Conditional Neural Processes
Makoto Kawano, Wataru Kumagai, Akiyoshi Sannai, Yusuke Iwasawa, Yutaka Matsuo
Poster
Tue 1:00 Risk-Averse Offline Reinforcement Learning
Núria Armengol Urpí, Sebastian Curi, Andreas Krause
Poster
Tue 1:00 Capturing Label Characteristics in VAEs
Tom W Joy, Sebastian Schmon, Philip Torr, Siddharth N, Tom Rainforth
Poster
Tue 1:00 Monte-Carlo Planning and Learning with Language Action Value Estimates
Youngsoo Jang, Seokin Seo, Jongmin Lee, Kee-Eung Kim
Poster
Tue 1:00 Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling
Đorđe Miladinović, Aleksandar Stanić, Stefan Bauer, Jürgen Schmidhuber, Joachim M Buhmann
Poster
Tue 1:00 Deep Repulsive Clustering of Ordered Data Based on Order-Identity Decomposition
Seon-Ho Lee, Chang-Su Kim
Poster
Tue 1:00 FedMix: Approximation of Mixup under Mean Augmented Federated Learning
Tehrim Yoon, Sumin Shin, Sung Ju Hwang, Eunho Yang
Poster
Tue 1:00 Bayesian Context Aggregation for Neural Processes
Michael Volpp, Fabian Flürenbrock, Lukas Grossberger, Christian Daniel, Gerhard Neumann
Poster
Tue 1:00 Practical Real Time Recurrent Learning with a Sparse Approximation
Jacob Menick, Erich Elsen, Utku Evci, Simon Osindero, Karen Simonyan, Alex Graves
Poster
Tue 1:00 Sample-Efficient Automated Deep Reinforcement Learning
Jörg Franke, Gregor Koehler, André Biedenkapp, Frank Hutter
Poster
Tue 1:00 Multiscale Score Matching for Out-of-Distribution Detection
Ahsan Mahmood, Junier Oliva, Martin A Styner
Poster
Tue 1:00 Generalized Energy Based Models
Michael Arbel, Liang Zhou, Arthur Gretton
Poster
Tue 1:00 PDE-Driven Spatiotemporal Disentanglement
Jérémie DONA, Jean-Yves Franceschi, sylvain lamprier, patrick gallinari
Poster
Tue 1:00 Coping with Label Shift via Distributionally Robust Optimisation
Jingzhao Zhang, Aditya Krishna Menon, Andreas Veit, Srinadh Bhojanapalli, Sanjiv Kumar, Suvrit Sra
Poster
Tue 1:00 Prediction and generalisation over directed actions by grid cells
Changmin Yu, Timothy Behrens, Neil Burgess
Poster
Tue 1:00 Class Normalization for (Continual)? Generalized Zero-Shot Learning
Ivan Skorokhodov, Mohamed Elhoseiny
Poster
Tue 1:00 Accurate Learning of Graph Representations with Graph Multiset Pooling
Jinheon Baek, Minki Kang, Sung Ju Hwang
Poster
Tue 1:00 On Self-Supervised Image Representations for GAN Evaluation
Stanislav Morozov, Andrey Voynov, Artem Babenko
Poster
Tue 1:00 Hyperbolic Neural Networks++
Ryohei Shimizu, YUSUKE Mukuta, Tatsuya Harada
Poster
Tue 1:00 BOIL: Towards Representation Change for Few-shot Learning
Jaehoon Oh, Hyungjun Yoo, ChangHwan Kim, Se-Young Yun
Oral
Tue 3:00 End-to-end Adversarial Text-to-Speech
Jeff Donahue, Sander Dieleman, Mikolaj Binkowski, Erich Elsen, Karen Simonyan
Oral
Tue 4:23 Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes
Mike Gartrell, Insu Han, Elvis Dohmatob, Jennifer Gillenwater, Victor-Emmanuel Brunel
Spotlight
Tue 4:38 Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows
Kashif Rasul, Abdul-Saboor Sheikh, Ingmar Schuster, Urs Bergmann, Roland Vollgraf
Spotlight
Tue 4:48 Noise against noise: stochastic label noise helps combat inherent label noise
Pengfei Chen, Guangyong Chen, Junjie Ye, jingwei zhao, Pheng-Ann Heng
Spotlight
Tue 5:08 Mutual Information State Intrinsic Control
Rui Zhao, Yang Gao, Pieter Abbeel, Volker Tresp, Wei Xu
Spotlight
Tue 5:18 Learning Incompressible Fluid Dynamics from Scratch - Towards Fast, Differentiable Fluid Models that Generalize
Nils Wandel, Michael Weinmann, Reinhard Klein
Tue 6:00 Lapsed Physicists Wine-and-Cheese (#1)
Invited Talk
Tue 8:00 AI in Finance: Scope and Examples
Manuela Veloso
Poster
Tue 9:00 On the Theory of Implicit Deep Learning: Global Convergence with Implicit Layers
Kenji Kawaguchi
Poster
Tue 9:00 Direction Matters: On the Implicit Bias of Stochastic Gradient Descent with Moderate Learning Rate
Jingfeng Wu, Difan Zou, vladimir braverman, Quanquan Gu
Poster
Tue 9:00 Meta-learning Symmetries by Reparameterization
Allan Zhou, Tom Knowles, Chelsea Finn
Poster
Tue 9:00 Supervised Contrastive Learning for Pre-trained Language Model Fine-tuning
Beliz Gunel, Jingfei Du, Alexis Conneau, Veselin Stoyanov
Poster
Tue 9:00 Decoupling Global and Local Representations via Invertible Generative Flows
Xuezhe Ma, Xiang Kong, Shanghang Zhang, Eduard H Hovy
Poster
Tue 9:00 SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments
Glen Berseth, Daniel Geng, Coline M Devin, Nicholas Rhinehart, Chelsea Finn, Dinesh Jayaraman, Sergey Levine
Poster
Tue 9:00 Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval
Lee Xiong, Chenyan Xiong, Ye Li, Kwok-Fung Tang, Jialin Liu, Paul N Bennett, Junaid Ahmed, Arnold Overwijk
Poster
Tue 9:00 Teaching with Commentaries
Aniruddh Raghu, Maithra Raghu, Simon Kornblith, David Duvenaud, Geoffrey Hinton
Poster
Tue 9:00 Rank the Episodes: A Simple Approach for Exploration in Procedurally-Generated Environments
Daochen Zha, Wenye Ma, Lei Yuan, Xia Hu, Ji Liu
Poster
Tue 9:00 On the Origin of Implicit Regularization in Stochastic Gradient Descent
Samuel Smith, Benoit Dherin, David Barrett, Soham De
Poster
Tue 9:00 Learning Neural Event Functions for Ordinary Differential Equations
Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel
Poster
Tue 9:00 Rethinking Attention with Performers
Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Richard Song, Georgiana-Andreea Gane, Tamas Sarlos, Peter Hawkins, Jared Q Davis, Afroz Mohiuddin, Lukasz Kaiser, David Belanger, Lucy J Colwell, Adrian Weller
Poster
Tue 9:00 Provable Rich Observation Reinforcement Learning with Combinatorial Latent States
Dipendra Misra, Qinghua Liu, Chi Jin, John Langford
Poster
Tue 9:00 How Benign is Benign Overfitting ?
Amartya Sanyal, Puneet Dokania, Varun Kanade, Philip Torr
Poster
Tue 9:00 Iterative Empirical Game Solving via Single Policy Best Response
Max Smith, Thomas Anthony, Michael Wellman
Poster
Tue 9:00 Quantifying Differences in Reward Functions
Adam Gleave, Michael Dennis, Shane Legg, Stuart Russell, Jan Leike
Poster
Tue 9:00 Sharper Generalization Bounds for Learning with Gradient-dominated Objective Functions
Yunwen Lei, Yiming Ying
Poster
Tue 9:00 Statistical inference for individual fairness
Subha Maity, Songkai Xue, Mikhail Yurochkin, Yuekai Sun
Poster
Tue 9:00 Vulnerability-Aware Poisoning Mechanism for Online RL with Unknown Dynamics
Yanchao Sun, Da Huo, Furong Huang
Poster
Tue 9:00 C-Learning: Horizon-Aware Cumulative Accessibility Estimation
Panteha Naderian, Gabriel Loaiza-Ganem, Harry Braviner, Anthony Caterini, Jesse C Cresswell, Tong Li, Animesh Garg
Poster
Tue 9:00 On the mapping between Hopfield networks and Restricted Boltzmann Machines
Matthew Smart, Anton Zilman
Poster
Tue 9:00 Distance-Based Regularisation of Deep Networks for Fine-Tuning
Henry Gouk, Timothy Hospedales, massimiliano pontil
Poster
Tue 9:00 Ringing ReLUs: Harmonic Distortion Analysis of Nonlinear Feedforward Networks
Christian Ali Mehmeti-Göpel, David Hartmann, Michael Wand
Poster
Tue 9:00 Getting a CLUE: A Method for Explaining Uncertainty Estimates
Javier Antorán, Umang Bhatt, Tameem Adel, Adrian Weller, José Miguel Hernández Lobato
Poster
Tue 9:00 Understanding Over-parameterization in Generative Adversarial Networks
Yogesh Balaji, Mohammadmahdi Sajedi, Neha Kalibhat, Mucong Ding, Dominik Stöger, Mahdi Soltanolkotabi, Soheil Feizi
Poster
Tue 9:00 DC3: A learning method for optimization with hard constraints
Priya Donti, David Rolnick, Zico Kolter
Poster
Tue 9:00 Reinforcement Learning with Random Delays
Yann Bouteiller, Simon Ramstedt, Giovanni Beltrame, Chris J Pal, Jonathan Binas
Poster
Tue 9:00 Self-Supervised Learning of Compressed Video Representations
Youngjae Yu, Sangho Lee, Gunhee Kim, Yale Song
Poster
Tue 9:00 Representation Learning via Invariant Causal Mechanisms
Jovana Mitrovic, Brian McWilliams, Jacob C Walker, Lars Buesing, Charles Blundell
Poster
Tue 9:00 Support-set bottlenecks for video-text representation learning
Mandela Patrick, Po-Yao Huang, Yuki Asano, Florian Metze, Alexander G Hauptmann, Joao F. Henriques, Andrea Vedaldi
Poster
Tue 9:00 Interpreting Knowledge Graph Relation Representation from Word Embeddings
Carl Allen, Ivana Balazevic, Timothy Hospedales
Poster
Tue 9:00 Learning Value Functions in Deep Policy Gradients using Residual Variance
Yannis Flet-Berliac, reda ouhamma, odalric-ambrym maillard, philippe preux
Poster
Tue 9:00 VTNet: Visual Transformer Network for Object Goal Navigation
Heming Du, Xin Yu, Liang Zheng
Poster
Tue 9:00 Towards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesis
Bingchen Liu, Yizhe Zhu, Kunpeng Song, Ahmed Elgammal
Poster
Tue 9:00 Learning Parametrised Graph Shift Operators
George Dasoulas, Johannes Lutzeyer, Michalis Vazirgiannis
Poster
Tue 9:00 Transient Non-stationarity and Generalisation in Deep Reinforcement Learning
Maximilian Igl, Gregory Farquhar, Jelena Luketina, Wendelin Boehmer, Shimon Whiteson
Poster
Tue 9:00 Physics-aware, probabilistic model order reduction with guaranteed stability
Sebastian Kaltenbach, PS Koutsourelakis
Poster
Tue 9:00 Anatomy of Catastrophic Forgetting: Hidden Representations and Task Semantics
Vinay Ramasesh, Ethan Dyer, Maithra Raghu
Poster
Tue 9:00 Learning Robust State Abstractions for Hidden-Parameter Block MDPs
Amy Zhang, Shagun Sodhani, Khimya Khetarpal, Joelle Pineau
Poster
Tue 9:00 FairBatch: Batch Selection for Model Fairness
Yuji Roh, Kangwook Lee, Steven Whang, Changho Suh
Poster
Tue 9:00 Discovering a set of policies for the worst case reward
Tom Zahavy, Andre Barreto, Daniel J Mankowitz, Shaobo Hou, Brendan ODonoghue, Iurii Kemaev, Satinder Singh
Poster
Tue 9:00 Scalable Bayesian Inverse Reinforcement Learning
Alex Chan, Mihaela van der Schaar
Poster
Tue 9:00 Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs
Jonathan Frankle, David J Schwab, Ari Morcos
Poster
Tue 9:00 Towards Resolving the Implicit Bias of Gradient Descent for Matrix Factorization: Greedy Low-Rank Learning
Zhiyuan Li, Yuping Luo, Kaifeng Lyu
Poster
Tue 9:00 SSD: A Unified Framework for Self-Supervised Outlier Detection
Vikash Sehwag, Mung Chiang, Prateek Mittal
Poster
Tue 9:00 Characterizing signal propagation to close the performance gap in unnormalized ResNets
Andrew Brock, Soham De, Samuel Smith
Poster
Tue 9:00 Tent: Fully Test-Time Adaptation by Entropy Minimization
Dequan Wang, Evan Shelhamer, Shaoteng Liu, Bruno Olshausen, trevor darrell
Poster
Tue 9:00 Clairvoyance: A Pipeline Toolkit for Medical Time Series
Dan Jarrett, Jinsung Yoon, Ioana Bica, Zhaozhi Qian, Ari Ercole, Mihaela van der Schaar
Poster
Tue 9:00 Data-Efficient Reinforcement Learning with Self-Predictive Representations
Max Schwarzer, Ankesh Anand, Rishab Goel, R Devon Hjelm, Aaron Courville, Philip Bachman
Poster
Tue 9:00 NOVAS: Non-convex Optimization via Adaptive Stochastic Search for End-to-end Learning and Control
Ioannis Exarchos, Marcus A Pereira, Ziyi Wang, Evangelos Theodorou
Poster
Tue 9:00 Are wider nets better given the same number of parameters?
Anna Golubeva, Guy Gur-Ari, Behnam Neyshabur
Poster
Tue 9:00 Text Generation by Learning from Demonstrations
Richard Pang, He He
Poster
Tue 9:00 Uncertainty-aware Active Learning for Optimal Bayesian Classifier
Guang Zhao, Edward Dougherty, Byung-Jun Yoon, Francis Alexander, Xiaoning Qian
Poster
Tue 9:00 Large Associative Memory Problem in Neurobiology and Machine Learning
Dmitry Krotov, John J Hopfield
Poster
Tue 9:00 Learning from Protein Structure with Geometric Vector Perceptrons
Bowen Jing, Stephan Eismann, Patricia Suriana, Raphael J Townshend, Ron Dror
Poster
Tue 9:00 Unsupervised Object Keypoint Learning using Local Spatial Predictability
Anand Gopalakrishnan, Sjoerd van Steenkiste, Jürgen Schmidhuber
Poster
Tue 9:00 Single-Timescale Actor-Critic Provably Finds Globally Optimal Policy
Zuyue Fu, Zhuoran Yang, Zhaoran Wang
Poster
Tue 9:00 Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding
Sana Tonekaboni, Danny Eytan, Anna Goldenberg
Poster
Tue 9:00 Auction Learning as a Two-Player Game
Jad Rahme, Samy Jelassi, S. M Weinberg
Poster
Tue 9:00 Transformer protein language models are unsupervised structure learners
Roshan Rao, Joshua Meier, Tom Sercu, Sergey Ovchinnikov, Alexander Rives
Poster
Tue 9:00 Recurrent Independent Mechanisms
Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, Bernhard Schoelkopf
Poster
Tue 9:00 Learning a Latent Search Space for Routing Problems using Variational Autoencoders
André Hottung, Bhanu Bhandari, Kevin Tierney
Poster
Tue 9:00 Robust Pruning at Initialization
Soufiane Hayou, Jean-Francois Ton, Arnaud Doucet, Yee Whye Teh
Oral
Tue 11:00 Iterated learning for emergent systematicity in VQA
Ankit Vani, Max Schwarzer, Yuchen Lu, Eeshan Dhekane, Aaron Courville
Oral
Tue 11:15 Learning Generalizable Visual Representations via Interactive Gameplay
Luca Weihs, Ani Kembhavi, Kiana Ehsani, Sarah M Pratt, Winson Han, Alvaro Herrasti, Eric Kolve, Dustin Schwenk, Roozbeh Mottaghi, Ali Farhadi
Spotlight
Tue 11:40 Recurrent Independent Mechanisms
Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, Bernhard Schoelkopf
Oral
Tue 12:00 Randomized Automatic Differentiation
Deniz Oktay, Nick McGreivy, Joshua Aduol, Alex Beatson, Ryan P Adams
Spotlight
Tue 12:40 Implicit Convex Regularizers of CNN Architectures: Convex Optimization of Two- and Three-Layer Networks in Polynomial Time
Tolga Ergen, Mert Pilanci
Spotlight
Tue 12:50 Learning from Protein Structure with Geometric Vector Perceptrons
Bowen Jing, Stephan Eismann, Patricia Suriana, Raphael J Townshend, Ron Dror
Oral
Tue 13:13 On the mapping between Hopfield networks and Restricted Boltzmann Machines
Matthew Smart, Anton Zilman
Spotlight
Tue 13:28 Learning-based Support Estimation in Sublinear Time
talyaa01 Eden, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner
Spotlight
Tue 13:38 Long-tail learning via logit adjustment
Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Himanshu Jain, Andreas Veit, Sanjiv Kumar
Expo Talk Panel
Tue 14:00 Interpretability with skeptical and user-centric mind
Been Kim
Poster
Tue 17:00 Learning to Reach Goals via Iterated Supervised Learning
Dibya Ghosh, Abhishek Gupta, Ashwin D Reddy, Justin Fu, Coline M Devin, Ben Eysenbach, Sergey Levine
Poster
Tue 17:00 Learning Safe Multi-agent Control with Decentralized Neural Barrier Certificates
Zengyi Qin, Kaiqing Zhang, chenyx Chen, Jingkai Chen, Chuchu Fan
Poster
Tue 17:00 Behavioral Cloning from Noisy Demonstrations
Fumihiro Sasaki, Ryota Yamashina
Poster
Tue 17:00 A Temporal Kernel Approach for Deep Learning with Continuous-time Information
Da Xu, Chuanwei Ruan, evren korpeoglu, Sushant Kumar, kannan achan
Poster
Tue 17:00 Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics
Daniel Kunin, Javier Sagastuy-Brena, Surya Ganguli, Daniel L Yamins, Hidenori Tanaka
Poster
Tue 17:00 Memory Optimization for Deep Networks
Aashaka Shah, Chao-Yuan Wu, Jayashree Mohan, Vijay Chidambaram, Philipp Krähenbühl
Poster
Tue 17:00 DrNAS: Dirichlet Neural Architecture Search
Xiangning Chen, Ruochen Wang, Minhao Cheng, Xiaocheng Tang, Cho-Jui Hsieh
Poster
Tue 17:00 Drop-Bottleneck: Learning Discrete Compressed Representation for Noise-Robust Exploration
Jaekyeom Kim, Minjung Kim, Dongyeon Woo, Gunhee Kim
Poster
Tue 17:00 Generalized Variational Continual Learning
Noel Loo, Siddharth Swaroop, Rich E Turner
Poster
Tue 17:00 How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision
Dongkwan Kim, Alice Oh
Poster
Tue 17:00 Information Laundering for Model Privacy
Xinran Wang, Yu Xiang, Jun Gao, Jie Ding
Poster
Tue 17:00 Usable Information and Evolution of Optimal Representations During Training
Michael Kleinman, Alessandro Achille, Daksh Idnani, Jonathan Kao
Poster
Tue 17:00 Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth
Thao Nguyen, Maithra Raghu, Simon Kornblith
Poster
Tue 17:00 Linear Mode Connectivity in Multitask and Continual Learning
Seyed Iman Mirzadeh, Mehrdad Farajtabar, Dilan Gorur, Razvan Pascanu, Hassan Ghasemzadeh
Poster
Tue 17:00 DDPNOpt: Differential Dynamic Programming Neural Optimizer
Guan-Horng Liu, Tianrong Chen, Evangelos Theodorou
Poster
Tue 17:00 Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning
Wonyong Jeong, Jaehong Yoon, Eunho Yang, Sung Ju Hwang
Poster
Tue 17:00 HalentNet: Multimodal Trajectory Forecasting with Hallucinative Intents
Deyao Zhu, Mohamed Zahran, Li Erran Li, Mohamed Elhoseiny
Poster
Tue 17:00 Knowledge Distillation as Semiparametric Inference
Tri Dao, Govinda Kamath, Vasilis Syrgkanis, Lester Mackey
Poster
Tue 17:00 Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity
Jang-Hyun Kim, Wonho Choo, Hosan Jeong, Hyun Oh Song
Poster
Tue 17:00 Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning
Aviral Kumar, Rishabh Agarwal, Dibya Ghosh, Sergey Levine
Poster
Tue 17:00 Why Are Convolutional Nets More Sample-Efficient than Fully-Connected Nets?
Zhiyuan Li, Yi Zhang, Sanjeev Arora
Poster
Tue 17:00 CompOFA – Compound Once-For-All Networks for Faster Multi-Platform Deployment
Manas Sahni, Shreya Varshini, Alind Khare, Alexey Tumanov
Poster
Tue 17:00 Concept Learners for Few-Shot Learning
Kaidi Cao, Maria Brbic, Jure Leskovec
Poster
Tue 17:00 BUSTLE: Bottom-Up Program Synthesis Through Learning-Guided Exploration
Augustus Odena, Kensen Shi, David Bieber, Rishabh Singh, Charles Sutton, Hanjun Dai
Poster
Tue 17:00 Are Neural Rankers still Outperformed by Gradient Boosted Decision Trees?
Zhen Qin, Le Yan, Honglei Zhuang, Yi Tay, Rama Kumar Pasumarthi, Xuanhui Wang, Michael Bendersky, Marc Najork
Poster
Tue 17:00 Large Batch Simulation for Deep Reinforcement Learning
Brennan Shacklett, Erik Wijmans, Aleksei Petrenko, Manolis Savva, Dhruv Batra, Vladlen Koltun, Kayvon Fatahalian
Poster
Tue 17:00 Dataset Inference: Ownership Resolution in Machine Learning
Pratyush Maini, Mohammad Yaghini, Nicolas Papernot
Poster
Tue 17:00 RMSprop converges with proper hyper-parameter
Naichen Shi, Dawei Li, Mingyi Hong, Ruoyu Sun
Poster
Tue 17:00 Fourier Neural Operator for Parametric Partial Differential Equations
Zongyi Li, Nikola B Kovachki, Kamyar Azizzadenesheli, Burigede liu, Kaushik Bhattacharya, Andrew Stuart, Anima Anandkumar
Poster
Tue 17:00 Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning
Haibo Yang, Minghong Fang, Jia Liu
Poster
Tue 17:00 FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning
Hong-You Chen, Wei-Lun Chao
Poster
Tue 17:00 Fuzzy Tiling Activations: A Simple Approach to Learning Sparse Representations Online
Yangchen Pan, Kirby Banman, Martha White
Poster
Tue 17:00 Hopper: Multi-hop Transformer for Spatiotemporal Reasoning
Honglu Zhou, Asim Kadav, Farley Lai, Alexandru Niculescu-Mizil, Martin Min, Mubbasir Kapadia, Hans P Graf
Poster
Tue 17:00 Aligning AI With Shared Human Values
Dan Hendrycks, Collin Burns, Steven Basart, Andrew Critch, Jerry Li, Dawn Song, Jacob Steinhardt
Poster
Tue 17:00 Understanding the role of importance weighting for deep learning
Da Xu, Yuting Ye, Chuanwei Ruan
Poster
Tue 17:00 Monotonic Kronecker-Factored Lattice
William Bakst, Nobuyuki Morioka, Erez Louidor
Poster
Tue 17:00 SEDONA: Search for Decoupled Neural Networks toward Greedy Block-wise Learning
Myeongjang Pyeon, Jihwan Moon, Taeyoung Hahn, Gunhee Kim
Poster
Tue 17:00 Discovering Non-monotonic Autoregressive Orderings with Variational Inference
Xuanlin Li, Brandon Trabucco, Dong Huk Park, Michael Luo, Sheng Shen, trevor darrell, Yang Gao
Poster
Tue 17:00 CoDA: Contrast-enhanced and Diversity-promoting Data Augmentation for Natural Language Understanding
Yanru Qu, Dinghan Shen, Yelong Shen, Sandra Sajeev, Weizhu Chen, Jiawei Han
Poster
Tue 17:00 DOP: Off-Policy Multi-Agent Decomposed Policy Gradients
Yihan Wang, Beining Han, Tonghan Wang, Heng Dong, Chongjie Zhang
Poster
Tue 17:00 Fantastic Four: Differentiable and Efficient Bounds on Singular Values of Convolution Layers
ssingla Singla, Soheil Feizi
Poster
Tue 17:00 The Importance of Pessimism in Fixed-Dataset Policy Optimization
Jacob Buckman, Carles Gelada, Marc G Bellemare
Poster
Tue 17:00 Bowtie Networks: Generative Modeling for Joint Few-Shot Recognition and Novel-View Synthesis
Zhipeng Bao, Yu-Xiong Wang, Martial Hebert
Poster
Tue 17:00 How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks
Keyulu Xu, Mozhi Zhang, Jingling Li, Simon Du, Ken-Ichi Kawarabayashi, Stefanie Jegelka
Poster
Tue 17:00 Attentional Constellation Nets for Few-Shot Learning
Weijian Xu, Yifan Xu, Huaijin Wang, Zhuowen Tu
Poster
Tue 17:00 Generating Adversarial Computer Programs using Optimized Obfuscations
Shashank Srikant, Sijia Liu, Tamara Mitrovska, Shiyu Chang, Quanfu Fan, Gaoyuan Zhang, Una-May O'Reilly
Poster
Tue 17:00 Deep Equals Shallow for ReLU Networks in Kernel Regimes
Alberto Bietti, Francis Bach
Poster
Tue 17:00 Implicit Convex Regularizers of CNN Architectures: Convex Optimization of Two- and Three-Layer Networks in Polynomial Time
Tolga Ergen, Mert Pilanci
Poster
Tue 17:00 A Discriminative Gaussian Mixture Model with Sparsity
Hideaki Hayashi, Seiichi Uchida
Poster
Tue 17:00 Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization
Michael Zhang, Tom Paine, Ofir Nachum, Cosmin Paduraru, George Tucker, ziyu wang, Mohammad Norouzi
Poster
Tue 17:00 Mathematical Reasoning via Self-supervised Skip-tree Training
Markus Rabe, Dennis Lee, Kshitij Bansal, Christian Szegedy
Poster
Tue 17:00 Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning
Tsung-Wei Ke, Jyh-Jing Hwang, Stella Yu
Poster
Tue 17:00 Gradient Descent on Neural Networks Typically Occurs at the Edge of Stability
Jeremy Cohen, Simran Kaur, Yuanzhi Li, Zico Kolter, Ameet Talwalkar
Poster
Tue 17:00 Individually Fair Rankings
Amanda Bower, Hamid Eftekhari, Mikhail Yurochkin, Yuekai Sun
Poster
Tue 17:00 Viewmaker Networks: Learning Views for Unsupervised Representation Learning
Alex Tamkin, Mike Wu, Noah Goodman
Poster
Tue 17:00 On Graph Neural Networks versus Graph-Augmented MLPs
Lei Chen, Zhengdao Chen, Joan Bruna
Poster
Tue 17:00 RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs
Meng Qu, Junkun Chen, Louis-Pascal A Xhonneux, Yoshua Bengio, Jian Tang
Poster
Tue 17:00 Can a Fruit Fly Learn Word Embeddings?
Yuchen Liang, Chaitanya Ryali, Ben Hoover, Leopold Grinberg, Saket Navlakha, Mohammed J Zaki, Dmitry Krotov
Poster
Tue 17:00 Discrete Graph Structure Learning for Forecasting Multiple Time Series
Chao Shang, Jie Chen, Jinbo Bi
Poster
Tue 17:00 Multi-resolution modeling of a discrete stochastic process identifies causes of cancer
Adam Yaari, Maxwell Sherman, Oliver C Priebe, Po-Ru Loh, Boris Katz, Andrei Barbu, Bonnie Berger
Oral
Tue 19:00 Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients
Brenden Petersen, Mikel Landajuela Larma, Terrell N Mundhenk, Claudio Santiago, Soo Kim, Joanne Kim
Spotlight
Tue 19:15 DDPNOpt: Differential Dynamic Programming Neural Optimizer
Guan-Horng Liu, Tianrong Chen, Evangelos Theodorou
Spotlight
Tue 19:35 Model-Based Visual Planning with Self-Supervised Functional Distances
Stephen Tian, Suraj Nair, Frederik Ebert, Sudeep Dasari, Ben Eysenbach, Chelsea Finn, Sergey Levine
Oral
Tue 19:55 Global Convergence of Three-layer Neural Networks in the Mean Field Regime
Huy Tuan Pham, Phan-Minh Nguyen
Spotlight
Tue 20:30 Individually Fair Gradient Boosting
Alexander Vargo, Fan Zhang, Mikhail Yurochkin, Yuekai Sun
Spotlight
Tue 20:40 Are Neural Rankers still Outperformed by Gradient Boosted Decision Trees?
Zhen Qin, Le Yan, Honglei Zhuang, Yi Tay, Rama Kumar Pasumarthi, Xuanhui Wang, Michael Bendersky, Marc Najork
Oral
Tue 21:03 Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity
Jang-Hyun Kim, Wonho Choo, Hosan Jeong, Hyun Oh Song
Oral
Tue 21:18 MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training
Beidi Chen, Zichang Liu, Binghui Peng, Zhaozhuo Xu, Jonathan L Li, Tri Dao, Zhao Song, Anshumali Shrivastava, Christopher Re
Spotlight
Tue 21:43 Memory Optimization for Deep Networks
Aashaka Shah, Chao-Yuan Wu, Jayashree Mohan, Vijay Chidambaram, Philipp Krähenbühl
Invited Talk
Wed 0:00 Perceiving the 3D World from Images and Video
Lourdes Agapito
Poster
Wed 1:00 Simple Spectral Graph Convolution
Hao Zhu, Piotr Koniusz
Poster
Wed 1:00 Self-supervised Adversarial Robustness for the Low-label, High-data Regime
Sven Gowal, Po-Sen Huang, Aaron v den, Timothy A Mann, Pushmeet Kohli
Poster
Wed 1:00 Explaining by Imitating: Understanding Decisions by Interpretable Policy Learning
Alihan Hüyük, Dan Jarrett, Cem Tekin, Mihaela van der Schaar
Poster
Wed 1:00 Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov Wasserstein
Khai Nguyen, Son Nguyen, Nhat Ho, Tung Pham, Hung Bui
Poster
Wed 1:00 A Better Alternative to Error Feedback for Communication-Efficient Distributed Learning
Samuel Horváth, Peter Richtarik
Poster
Wed 1:00 Long Range Arena : A Benchmark for Efficient Transformers
Yi Tay, Mostafa Dehghani, Samira Abnar, Yikang Shen, Dara Bahri, Philip Pham, Jinfeng Rao, Liu Yang, Sebastian Ruder, Donald Metzler
Poster
Wed 1:00 Active Contrastive Learning of Audio-Visual Video Representations
Shuang Ma, Zhaoyang Zeng, Daniel McDuff, Yale Song
Poster
Wed 1:00 Explainable Deep One-Class Classification
Philipp Liznerski, Lukas Ruff, Robert A Vandermeulen, Billy J Franks, Marius Kloft, Klaus R Muller
Poster
Wed 1:00 Grounded Language Learning Fast and Slow
Felix Hill, Olivier Tieleman, Tamara von Glehn, Nathaniel Wong, Hamza Merzic, Stephen Clark
Poster
Wed 1:00 DICE: Diversity in Deep Ensembles via Conditional Redundancy Adversarial Estimation
Alexandre Rame, MATTHIEU CORD
Poster
Wed 1:00 IEPT: Instance-Level and Episode-Level Pretext Tasks for Few-Shot Learning
Manli Zhang, Jianhong Zhang, Zhiwu Lu, Tao Xiang, Mingyu Ding, Songfang Huang
Poster
Wed 1:00 Learning from Demonstration with Weakly Supervised Disentanglement
Yordan Hristov, Subramanian Ramamoorthy
Poster
Wed 1:00 Discovering Diverse Multi-Agent Strategic Behavior via Reward Randomization
Zhenggang Tang, Chao Yu, Boyuan Chen, Huazhe Xu, Xiaolong Wang, Fei Fang, Simon Du, Yu Wang, Yi Wu
Poster
Wed 1:00 Deep Neural Network Fingerprinting by Conferrable Adversarial Examples
Nils Lukas, Yuxuan Zhang, Florian Kerschbaum
Poster
Wed 1:00 Dance Revolution: Long-Term Dance Generation with Music via Curriculum Learning
Ruozi Huang, Huang Hu, Wei Wu, Kei Sawada, Mi Zhang, Daxin Jiang
Poster
Wed 1:00 Learning Associative Inference Using Fast Weight Memory
Imanol Schlag, Tsendsuren Munkhdalai, Jürgen Schmidhuber
Poster
Wed 1:00 Net-DNF: Effective Deep Modeling of Tabular Data
Liran Katzir, Gal Elidan, Ran El-Yaniv
Poster
Wed 1:00 Neural networks with late-phase weights
Johannes von Oswald, Seijin Kobayashi, Joao Sacramento, Alexander Meulemans, Christian Henning, Benjamin F Grewe
Poster
Wed 1:00 Differentiable Segmentation of Sequences
Erik Scharwächter, Jonathan Lennartz, Emmanuel Müller
Poster
Wed 1:00 Neural ODE Processes
Alexander Norcliffe, Cristian Bodnar, Ben Day, Jacob Moss, Pietro Liò
Poster
Wed 1:00 Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
Yuan Yin, Vincent Le Guen, Jérémie DONA, Emmanuel d Bezenac, Ibrahim Ayed, Nicolas THOME, patrick gallinari
Poster
Wed 1:00 Graph Edit Networks
Benjamin Paassen, Daniele Grattarola, Daniele Zambon, Cesare Alippi, Barbara E Hammer
Poster
Wed 1:00 Separation and Concentration in Deep Networks
John Zarka, Florentin Guth, Stéphane Mallat
Poster
Wed 1:00 Auxiliary Task Update Decomposition: The Good, the Bad and the Neutral
Lucio Dery, Yann Dauphin, David Grangier
Poster
Wed 1:00 FOCAL: Efficient Fully-Offline Meta-Reinforcement Learning via Distance Metric Learning and Behavior Regularization
Lanqing Li, Rui Yang, Dijun Luo
Poster
Wed 1:00 Negative Data Augmentation
Abhishek Sinha, Kumar Ayush, Jiaming Song, Burak Uzkent, Hongxia Jin, Stefano Ermon
Poster
Wed 1:00 Deep Learning meets Projective Clustering
Alaa Maalouf, Harry Lang, Daniela Rus, Dan Feldman
Poster
Wed 1:00 Efficient Continual Learning with Modular Networks and Task-Driven Priors
Tom Veniat, Ludovic Denoyer, Marc'Aurelio Ranzato
Poster
Wed 1:00 Robust Learning of Fixed-Structure Bayesian Networks in Nearly-Linear Time
Yu Cheng, Honghao Lin
Poster
Wed 1:00 Improving Adversarial Robustness via Channel-wise Activation Suppressing
Yang Bai, Yuyuan Zeng, Yong Jiang, Shu-Tao Xia, Daniel Ma, Yisen Wang
Poster
Wed 1:00 Geometry-aware Instance-reweighted Adversarial Training
Jingfeng Zhang, Jianing ZHU, Gang Niu, Bo Han, Masashi Sugiyama, Mohan Kankanhalli
Poster
Wed 1:00 Isometric Propagation Network for Generalized Zero-shot Learning
Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Xuanyi Dong, Chengqi Zhang
Poster
Wed 1:00 Return-Based Contrastive Representation Learning for Reinforcement Learning
Guoqing Liu, Chuheng Zhang, Li Zhao, Tao Qin, Jinhua Zhu, Li Jian, Nenghai Yu, Tie-Yan Liu
Poster
Wed 1:00 Gradient Origin Networks
Sam Bond-Taylor, Chris G Willcocks
Poster
Wed 1:00 Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models
Yuge Shi, Brooks Paige, Philip Torr, Siddharth N
Poster
Wed 1:00 Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization
Tatsuya Matsushima, Hiroki Furuta, Yutaka Matsuo, Ofir Nachum, Shixiang Gu
Poster
Wed 1:00 Communication in Multi-Agent Reinforcement Learning: Intention Sharing
WOOJUN KIM, Jongeui Park, Youngchul Sung
Poster
Wed 1:00 Identifying Physical Law of Hamiltonian Systems via Meta-Learning
Seungjun Lee, Haesang Yang, Woojae Seong
Poster
Wed 1:00 On Data-Augmentation and Consistency-Based Semi-Supervised Learning
Atin Ghosh, alexandre thiery
Poster
Wed 1:00 Removing Undesirable Feature Contributions Using Out-of-Distribution Data
Saehyung Lee, Changhwa Park, Hyungyu Lee, Jihun Yi, Jonghyun Lee, Sungroh Yoon
Poster
Wed 1:00 Byzantine-Resilient Non-Convex Stochastic Gradient Descent
Zeyuan Allen-Zhu, Faeze Ebrahimianghazani, Jerry Li, Dan Alistarh
Poster
Wed 1:00 Disentangled Recurrent Wasserstein Autoencoder
Jun Han, Martin Min, Ligong Han, Li Erran Li, Xuan Zhang
Poster
Wed 1:00 Learning Task Decomposition with Ordered Memory Policy Network
Yuchen Lu, Yikang Shen, Siyuan Zhou, Aaron Courville, Joshua B Tenenbaum, Chuang Gan
Poster
Wed 1:00 Knowledge distillation via softmax regression representation learning
Jing Yang, Brais Martinez, Adrian Bulat, Georgios Tzimiropoulos
Poster
Wed 1:00 CoCon: A Self-Supervised Approach for Controlled Text Generation
Alvin Chan, Yew-Soon Ong, Bill Pung, Aston Zhang, Jie Fu
Poster
Wed 1:00 New Bounds For Distributed Mean Estimation and Variance Reduction
Peter Davies, Vijaykrishna Gurunathan, Niusha Moshrefi, Saleh Ashkboos, Dan Alistarh
Poster
Wed 1:00 Acting in Delayed Environments with Non-Stationary Markov Policies
Esther Derman, Gal Dalal, Shie Mannor
Poster
Wed 1:00 High-Capacity Expert Binary Networks
Adrian Bulat, Brais Martinez, Georgios Tzimiropoulos
Oral
Wed 3:15 Rethinking Attention with Performers
Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Richard Song, Georgiana-Andreea Gane, Tamas Sarlos, Peter Hawkins, Jared Q Davis, Afroz Mohiuddin, Lukasz Kaiser, David Belanger, Lucy J Colwell, Adrian Weller
Oral
Wed 3:30 Share or Not? Learning to Schedule Language-Specific Capacity for Multilingual Translation
Biao Zhang, Ankur Bapna, Rico Sennrich, Orhan Firat
Spotlight
Wed 3:45 Support-set bottlenecks for video-text representation learning
Mandela Patrick, Po-Yao Huang, Yuki Asano, Florian Metze, Alexander G Hauptmann, Joao F. Henriques, Andrea Vedaldi
Oral
Wed 4:05 Getting a CLUE: A Method for Explaining Uncertainty Estimates
Javier Antorán, Umang Bhatt, Tameem Adel, Adrian Weller, José Miguel Hernández Lobato
Spotlight
Wed 4:20 Influence Estimation for Generative Adversarial Networks
Naoyuki Terashita, Hiroki Ohashi, Yuichi Nonaka, Takashi Kanemaru
Spotlight
Wed 4:40 Deep Neural Network Fingerprinting by Conferrable Adversarial Examples
Nils Lukas, Yuxuan Zhang, Florian Kerschbaum
Oral
Wed 5:00 Learning Cross-Domain Correspondence for Control with Dynamics Cycle-Consistency
Qiang Zhang, Tete Xiao, Alyosha Efros, Lerrel Pinto, Xiaolong Wang
Spotlight
Wed 5:15 Benefit of deep learning with non-convex noisy gradient descent: Provable excess risk bound and superiority to kernel methods
Taiji Suzuki, Akiyama Shunta
Spotlight
Wed 5:25 Tent: Fully Test-Time Adaptation by Entropy Minimization
Dequan Wang, Evan Shelhamer, Shaoteng Liu, Bruno Olshausen, trevor darrell
Spotlight
Wed 5:35 Neural Approximate Sufficient Statistics for Implicit Models
Yanzhi Chen, Dinghuai Zhang, Michael U Gutmann, Aaron Courville, Zhanxing Zhu
Invited Talk
Wed 8:00 Is My Dataset Biased?
Kate Saenko
Poster
Wed 9:00 Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF
Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt, Justin Bayer
Poster
Wed 9:00 Mastering Atari with Discrete World Models
Danijar Hafner, Timothy Lillicrap, Mohammad Norouzi, Jimmy Ba
Poster
Wed 9:00 Learning to Represent Action Values as a Hypergraph on the Action Vertices
Arash Tavakoli, Mehdi Fatemi, Petar Kormushev
Poster
Wed 9:00 Learning Mesh-Based Simulation with Graph Networks
Tobias Pfaff, Meire Fortunato, Alvaro Sanchez Gonzalez, Peter Battaglia
Poster
Wed 9:00 Entropic gradient descent algorithms and wide flat minima
Fabrizio Pittorino, Carlo Lucibello, Christoph Feinauer, Gabriele Perugini, Carlo Baldassi, Elizaveta Demyanenko, Riccardo Zecchina
Poster
Wed 9:00 Human-Level Performance in No-Press Diplomacy via Equilibrium Search
Jonathan Gray, Adam Lerer, Anton Bakhtin, Noam Brown
Poster
Wed 9:00 RODE: Learning Roles to Decompose Multi-Agent Tasks
Tonghan Wang, Tarun Gupta, Anuj Mahajan, Bei Peng, Shimon Whiteson, Chongjie Zhang
Poster
Wed 9:00 Exploring the Uncertainty Properties of Neural Networks’ Implicit Priors in the Infinite-Width Limit
Ben Adlam, Jaehoon Lee, Lechao Xiao, Jeffrey Pennington, Jasper Snoek
Poster
Wed 9:00 SEED: Self-supervised Distillation For Visual Representation
Jacob Zhiyuan Fang, Jianfeng Wang, Lijuan Wang, Lei Zhang, 'YZ' Yezhou Yang, Zicheng Liu
Poster
Wed 9:00 Unsupervised Audiovisual Synthesis via Exemplar Autoencoders
Kangle Deng, Aayush Bansal, Deva Ramanan
Poster
Wed 9:00 Theoretical bounds on estimation error for meta-learning
James Lucas, Mengye Ren, Irene Raissa KAMENI KAMENI, Toniann Pitassi, Richard Zemel
Poster
Wed 9:00 You Only Need Adversarial Supervision for Semantic Image Synthesis
Edgar Schoenfeld, Vadim Sushko, Dan Zhang, Juergen Gall, Bernt Schiele, Anna Khoreva
Poster
Wed 9:00 Learning Generalizable Visual Representations via Interactive Gameplay
Luca Weihs, Ani Kembhavi, Kiana Ehsani, Sarah M Pratt, Winson Han, Alvaro Herrasti, Eric Kolve, Dustin Schwenk, Roozbeh Mottaghi, Ali Farhadi
Poster
Wed 9:00 Ask Your Humans: Using Human Instructions to Improve Generalization in Reinforcement Learning
Valerie Chen, Abhinav Gupta, Kenny Marino
Poster
Wed 9:00 Long-tail learning via logit adjustment
Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Himanshu Jain, Andreas Veit, Sanjiv Kumar
Poster
Wed 9:00 Property Controllable Variational Autoencoder via Invertible Mutual Dependence
Xiaojie Guo, Yuanqi Du, Liang Zhao
Poster
Wed 9:00 My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control
Vitaly Kurin, Maximilian Igl, Tim Rocktaeschel, Wendelin Boehmer, Shimon Whiteson
Poster
Wed 9:00 Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms
Maruan Al-Shedivat, Jennifer Gillenwater, Eric P Xing, Afshin Rostamizadeh
Poster
Wed 9:00 HyperGrid Transformers: Towards A Single Model for Multiple Tasks
Yi Tay, Zhe Zhao, Dara Bahri, Donald Metzler, DA-CHENG Juan
Poster
Wed 9:00 Differentiable Trust Region Layers for Deep Reinforcement Learning
Fabian Otto, Philipp Becker, Vien A Ngo, Hanna Ziesche, Gerhard Neumann
Poster
Wed 9:00 Boost then Convolve: Gradient Boosting Meets Graph Neural Networks
Sergei Ivanov, Liudmila Prokhorenkova
Poster
Wed 9:00 Graph Information Bottleneck for Subgraph Recognition
Junchi Yu, Tingyang Xu, Yu Rong, Yatao Bian, Junzhou Huang, Ran He
Poster
Wed 9:00 TropEx: An Algorithm for Extracting Linear Terms in Deep Neural Networks
Martin Trimmel, Henning Petzka, Cristian Sminchisescu
Poster
Wed 9:00 IsarStep: a Benchmark for High-level Mathematical Reasoning
Wenda Li, Lei Yu, Yuhuai Wu, Lawrence Paulson
Poster
Wed 9:00 Average-case Acceleration for Bilinear Games and Normal Matrices
Carles Domingo i Enrich, Fabian Pedregosa, Damien Scieur
Poster
Wed 9:00 Learning Task-General Representations with Generative Neuro-Symbolic Modeling
Reuben Feinman, Brenden Lake
Poster
Wed 9:00 Growing Efficient Deep Networks by Structured Continuous Sparsification
Xin Yuan, Pedro Savarese, Michael Maire
Poster
Wed 9:00 Benchmarks for Deep Off-Policy Evaluation
Justin Fu, Mohammad Norouzi, Ofir Nachum, George Tucker, ziyu wang, Alexander Novikov, Sherry Yang, Michael Zhang, Yutian Chen, Aviral Kumar, Cosmin Paduraru, Sergey Levine, Tom Paine
Poster
Wed 9:00 Geometry-Aware Gradient Algorithms for Neural Architecture Search
Liam Li, Misha Khodak, Nina Balcan, Ameet Talwalkar
Poster
Wed 9:00 DeepAveragers: Offline Reinforcement Learning By Solving Derived Non-Parametric MDPs
aayam shrestha, Stefan Lee, Prasad Tadepalli, Alan Fern
Poster
Wed 9:00 Self-supervised Visual Reinforcement Learning with Object-centric Representations
Andrii Zadaianchuk, Maximilian Seitzer, Georg Martius
Poster
Wed 9:00 Anchor & Transform: Learning Sparse Embeddings for Large Vocabularies
Paul Pu Liang, Manzil Zaheer, Yuan Wang, Amr Ahmed
Poster
Wed 9:00 Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows
Kashif Rasul, Abdul-Saboor Sheikh, Ingmar Schuster, Urs Bergmann, Roland Vollgraf
Poster
Wed 9:00 Coupled Oscillatory Recurrent Neural Network (coRNN): An accurate and (gradient) stable architecture for learning long time dependencies
T. Konstantin Rusch, Siddhartha Mishra
Poster
Wed 9:00 For self-supervised learning, Rationality implies generalization, provably
Yamini Bansal, Gal Kaplun, Boaz Barak
Poster
Wed 9:00 Few-Shot Bayesian Optimization with Deep Kernel Surrogates
Martin Wistuba, Josif Grabocka
Poster
Wed 9:00 Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients
Brenden Petersen, Mikel Landajuela Larma, Terrell N Mundhenk, Claudio Santiago, Soo Kim, Joanne Kim
Poster
Wed 9:00 Chaos of Learning Beyond Zero-sum and Coordination via Game Decompositions
Yun Kuen Cheung, Yixin Tao
Poster
Wed 9:00 Are Neural Nets Modular? Inspecting Functional Modularity Through Differentiable Weight Masks
Robert Csordas, Sjoerd van Steenkiste, Jürgen Schmidhuber
Poster
Wed 9:00 Modeling the Second Player in Distributionally Robust Optimization
Paul Michel, Tatsunori Hashimoto, Graham Neubig
Poster
Wed 9:00 Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning
Elan Markowitz, Keshav Balasubramanian, Mehrnoosh Mirtaheri, Sami Abu-El-Haija, Bryan Perozzi, Greg Ver Steeg, Aram Galstyan
Poster
Wed 9:00 Optimism in Reinforcement Learning with Generalized Linear Function Approximation
Yining Wang, Ruosong Wang, Simon Du, Akshay Krishnamurthy
Poster
Wed 9:00 Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching
Jonas Geiping, Liam H Fowl, Ronny Huang, Wojciech Czaja, Gavin Taylor, Michael Moeller, Tom Goldstein
Poster
Wed 9:00 Probabilistic Numeric Convolutional Neural Networks
Marc Finzi, Roberto Bondesan, Max Welling
Poster
Wed 9:00 Learning advanced mathematical computations from examples
François Charton, Amaury Hayat, Guillaume Lample
Poster
Wed 9:00 OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning
Anurag Ajay, Aviral Kumar, Pulkit Agrawal, Sergey Levine, Ofir Nachum
Poster
Wed 9:00 Neural Networks for Learning Counterfactual G-Invariances from Single Environments
S Chandra Mouli, Bruno Ribeiro
Poster
Wed 9:00 Pre-training Text-to-Text Transformers for Concept-centric Common Sense
Wangchunshu Zhou, Dong-Ho Lee, Ravi Kiran Selvam, Seyeon Lee, Xiang Ren
Poster
Wed 9:00 Provably robust classification of adversarial examples with detection
Fatemeh Sheikholeslami, Ali Lotfi, Zico Kolter
Poster
Wed 9:00 More or Less: When and How to Build Convolutional Neural Network Ensembles
Abdul Wasay, Stratos Idreos
Poster
Wed 9:00 Iterated learning for emergent systematicity in VQA
Ankit Vani, Max Schwarzer, Yuchen Lu, Eeshan Dhekane, Aaron Courville
Poster
Wed 9:00 Evaluation of Neural Architectures Trained With Square Loss vs Cross-Entropy in Classification Tasks
Like Hui, Misha Belkin
Poster
Wed 9:00 HyperDynamics: Meta-Learning Object and Agent Dynamics with Hypernetworks
Zhou Xian, Shamit Lal, Hsiao-Yu Tung, Anthony Platanios, Katerina Fragkiadaki
Poster
Wed 9:00 Sharpness-aware Minimization for Efficiently Improving Generalization
Pierre Foret, Ariel Kleiner, Hossein Mobahi, Behnam Neyshabur
Poster
Wed 9:00 Watch-And-Help: A Challenge for Social Perception and Human-AI Collaboration
Xavier Puig, Tianmin Shu, Shuang Li, Zilin Wang, Andrew Liao, Joshua B Tenenbaum, Sanja Fidler, Antonio Torralba
Poster
Wed 9:00 Unbiased Teacher for Semi-Supervised Object Detection
Yen-Cheng Liu, Chih-Yao Ma, Zijian He, Chia-Wen Kuo, Kan Chen, Peizhao Zhang, Bichen Wu, Zsolt Kira, Peter Vajda
Poster
Wed 9:00 Sliced Kernelized Stein Discrepancy
Wenbo Gong, Yingzhen Li, José Miguel Hernández Lobato
Oral
Wed 11:00 Human-Level Performance in No-Press Diplomacy via Equilibrium Search
Jonathan Gray, Adam Lerer, Anton Bakhtin, Noam Brown
Oral
Wed 11:15 Learning to Reach Goals via Iterated Supervised Learning
Dibya Ghosh, Abhishek Gupta, Ashwin D Reddy, Justin Fu, Coline M Devin, Ben Eysenbach, Sergey Levine
Oral
Wed 11:30 Learning Invariant Representations for Reinforcement Learning without Reconstruction
Amy Zhang, Rowan T McAllister, Roberto Calandra, Yarin Gal, Sergey Levine
Oral
Wed 11:45 Evolving Reinforcement Learning Algorithms
John Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Quoc V Le, Sergey Levine, Honglak Lee, Aleksandra Faust
Spotlight
Wed 12:00 Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels
Denis Yarats, Ilya Kostrikov, Rob Fergus
Wed 12:00 Women in Artificial Intelligence & Machine Learning (WinAIML)
Oral
Wed 12:23 Coupled Oscillatory Recurrent Neural Network (coRNN): An accurate and (gradient) stable architecture for learning long time dependencies
T. Konstantin Rusch, Siddhartha Mishra
Spotlight
Wed 12:48 LambdaNetworks: Modeling long-range Interactions without Attention
Irwan Bello
Spotlight
Wed 12:58 Grounded Language Learning Fast and Slow
Felix Hill, Olivier Tieleman, Tamara von Glehn, Nathaniel Wong, Hamza Merzic, Stephen Clark
Spotlight
Wed 13:18 Unsupervised Object Keypoint Learning using Local Spatial Predictability
Anand Gopalakrishnan, Sjoerd van Steenkiste, Jürgen Schmidhuber
Spotlight
Wed 13:38 Dynamic Tensor Rematerialization
Marisa Kirisame, Steven S. Lyubomirsky, Altan Haan, Jennifer Brennan, Mike He, Jared G Roesch, Tianqi Chen, Zachary Tatlock
Spotlight
Wed 13:58 Differentially Private Learning Needs Better Features (or Much More Data)
Florian Tramer, Dan Boneh
Expo Talk Panel
Wed 14:00 Live Panel - Academics@ Presents: Representation Learning at Amazon
Zahra Matson
Spotlight
Wed 16:45 Learning Mesh-Based Simulation with Graph Networks
Tobias Pfaff, Meire Fortunato, Alvaro Sanchez Gonzalez, Peter Battaglia
Poster
Wed 17:00 gradSim: Differentiable simulation for system identification and visuomotor control
Krishna Murthy Jatavallabhula, Miles Macklin, Florian Golemo, Vikram Voleti, Linda Petrini, Martin Weiss, Breandan Considine, Jérôme Parent-Lévesque, Kevin Xie, Kenny Erleben, Liam Paull, Florian Shkurti, Derek Nowrouzezahrai, Sanja Fidler
Poster
Wed 17:00 Beyond Fully-Connected Layers with Quaternions: Parameterization of Hypercomplex Multiplications with $1/n$ Parameters
Aston Zhang, Yi Tay, Shuai Zhang, Alvin Chan, Anh Tuan Luu, Siu Hui, Jie Fu
Poster
Wed 17:00 Better Fine-Tuning by Reducing Representational Collapse
Armen Aghajanyan, Akshat Shrivastava, Anchit Gupta, Naman Goyal, Luke Zettlemoyer, Sonal Gupta
Poster
Wed 17:00 Control-Aware Representations for Model-based Reinforcement Learning
Brandon Cui, Yinlam Chow, Mohammad Ghavamzadeh
Poster
Wed 17:00 BERTology Meets Biology: Interpreting Attention in Protein Language Models
Jesse Vig, Ali Madani, Lav R Varshney, Caiming Xiong, Richard Socher, Nazneen Rajani
Poster
Wed 17:00 Learning with Feature-Dependent Label Noise: A Progressive Approach
Yikai Zhang, Songzhu Zheng, Pengxiang Wu, Mayank Goswami, Chao Chen
Poster
Wed 17:00 Evolving Reinforcement Learning Algorithms
John Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Quoc V Le, Sergey Levine, Honglak Lee, Aleksandra Faust
Poster
Wed 17:00 On the Critical Role of Conventions in Adaptive Human-AI Collaboration
Andy Shih, Arjun Sawhney, Jovana Kondic, Stefano Ermon, Dorsa Sadigh
Poster
Wed 17:00 AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on the Fly
Yuchen Jin, Tianyi Zhou, Liangyu Zhao, Yibo Zhu, Chuanxiong Guo, Marco Canini, Arvind Krishnamurthy
Poster
Wed 17:00 Combining Physics and Machine Learning for Network Flow Estimation
Arlei Lopes da Silva, Furkan Kocayusufoglu, Saber Jafarpour, Francesco Bullo, Ananthram Swami, Ambuj K Singh
Poster
Wed 17:00 CPR: Classifier-Projection Regularization for Continual Learning
Sungmin Cha, Hsiang Hsu, Taebaek Hwang, Flavio Calmon, Taesup Moon
Poster
Wed 17:00 Local Convergence Analysis of Gradient Descent Ascent with Finite Timescale Separation
Tanner Fiez, Lillian J Ratliff
Poster
Wed 17:00 Fast And Slow Learning Of Recurrent Independent Mechanisms
Kanika Madan, Nan Rosemary Ke, Anirudh Goyal, Bernhard Schoelkopf, Yoshua Bengio
Poster
Wed 17:00 Wandering within a world: Online contextualized few-shot learning
Mengye Ren, Michael L Iuzzolino, Mike Mozer, Richard Zemel
Poster
Wed 17:00 Beyond Categorical Label Representations for Image Classification
Boyuan Chen, Yu Li, Sunand Raghupathi, Hod Lipson
Poster
Wed 17:00 Modelling Hierarchical Structure between Dialogue Policy and Natural Language Generator with Option Framework for Task-oriented Dialogue System
Jianhong Wang, Yuan Zhang, Tae-Kyun Kim, Yunjie Gu
Poster
Wed 17:00 Task-Agnostic Morphology Evolution
Donald Hejna III, Pieter Abbeel, Lerrel Pinto
Poster
Wed 17:00 Efficient Reinforcement Learning in Factored MDPs with Application to Constrained RL
Xiaoyu Chen, Jiachen Hu, Lihong Li, Liwei Wang
Poster
Wed 17:00 ALFWorld: Aligning Text and Embodied Environments for Interactive Learning
Mohit Shridhar, Eric Yuan, Marc-Alexandre Cote, Yonatan Bisk, Adam Trischler, Matthew Hausknecht
Poster
Wed 17:00 Learning and Evaluating Representations for Deep One-Class Classification
Kihyuk Sohn, Chun-Liang Li, Jinsung Yoon, Minho Jin, Tomas Pfister
Poster
Wed 17:00 Emergent Symbols through Binding in External Memory
Taylor Webb, Ishan Sinha, Jonathan Cohen
Poster
Wed 17:00 Learning Manifold Patch-Based Representations of Man-Made Shapes
Dmitriy Smirnov, Mikhail Bessmeltsev, Justin Solomon
Poster
Wed 17:00 Filtered Inner Product Projection for Crosslingual Embedding Alignment
Vin Sachidananda, Ziyi Yang, Chenguang Zhu
Poster
Wed 17:00 In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness
Sang Michael Xie, Ananya Kumar, Robbie Jones, Fereshte Khani, Tengyu Ma, Percy Liang
Poster
Wed 17:00 Evaluating the Disentanglement of Deep Generative Models through Manifold Topology
Sharon Zhou, Eric Zelikman, Fred Lu, Andrew Ng, Gunnar E Carlsson, Stefano Ermon
Poster
Wed 17:00 Learning with Instance-Dependent Label Noise: A Sample Sieve Approach
Hao Cheng, Zhaowei Zhu, Xingyu Li, Yifei Gong, Xing Sun, Yang Liu
Poster
Wed 17:00 Adaptive Universal Generalized PageRank Graph Neural Network
Eli Chien, Jianhao Peng, Pan Li, Olgica Milenkovic
Poster
Wed 17:00 Influence Functions in Deep Learning Are Fragile
Samyadeep Basu, Phil Pope, Soheil Feizi
Poster
Wed 17:00 Individually Fair Gradient Boosting
Alexander Vargo, Fan Zhang, Mikhail Yurochkin, Yuekai Sun
Poster
Wed 17:00 Learning to Generate 3D Shapes with Generative Cellular Automata
Dongsu Zhang, Changwoon Choi, Jeonghwan Kim, Young Min Kim
Poster
Wed 17:00 Mixed-Features Vectors and Subspace Splitting
Alejandro Pimentel-Alarcón, Daniel L Pimentel-Alarcón
Poster
Wed 17:00 Graph-Based Continual Learning
Binh Tang, David S Matteson
Poster
Wed 17:00 Efficient Wasserstein Natural Gradients for Reinforcement Learning
Ted Moskovitz, Michael Arbel, Ferenc Huszar, Arthur Gretton
Poster
Wed 17:00 Generating Furry Cars: Disentangling Object Shape and Appearance across Multiple Domains
Utkarsh Ojha, Krishna Kumar Singh, Yong Jae Lee
Poster
Wed 17:00 Revisiting Dynamic Convolution via Matrix Decomposition
Yunsheng Li, Yinpeng Chen, Xiyang Dai, mengchen liu, Dongdong Chen, Ye Yu, Lu Yuan, Zicheng Liu, Mei Chen, Nuno Vasconcelos
Poster
Wed 17:00 Explainable Subgraph Reasoning for Forecasting on Temporal Knowledge Graphs
Zhen Han, Peng Chen, Yunpu Ma, Volker Tresp
Poster
Wed 17:00 INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving
Yuhuai Wu, Albert Jiang, Jimmy Ba, Roger Grosse
Poster
Wed 17:00 Estimating Lipschitz constants of monotone deep equilibrium models
Chirag Pabbaraju, Ezra Winston, Zico Kolter
Poster
Wed 17:00 NBDT: Neural-Backed Decision Tree
Alvin Wan, Lisa Dunlap, Daniel Ho, Jihan Yin, Scott Lee, Suzanne Petryk, Sarah A Bargal, Joseph E Gonzalez
Poster
Wed 17:00 Learning to Deceive Knowledge Graph Augmented Models via Targeted Perturbation
Mrigank Raman, Aaron Chan, Siddhant Agarwal, PeiFeng Wang, Hansen Wang, Sungchul Kim, Ryan Rossi, Handong Zhao, Nedim Lipka, Xiang Ren
Poster
Wed 17:00 Learning Long-term Visual Dynamics with Region Proposal Interaction Networks
Haozhi Qi, Xiaolong Wang, Deepak Pathak, Yi Ma, Jitendra Malik
Poster
Wed 17:00 Protecting DNNs from Theft using an Ensemble of Diverse Models
Sanjay Kariyappa, Atul Prakash, Moinuddin K Qureshi
Poster
Wed 17:00 PolarNet: Learning to Optimize Polar Keypoints for Keypoint Based Object Detection
xwwu xiongwei, Doyen Sahoo, Steven HOI
Poster
Wed 17:00 Is Attention Better Than Matrix Decomposition?
Zhengyang Geng, Meng-Hao Guo, Hongxu Chen, Xia Li, Ke Wei, Zhouchen Lin
Poster
Wed 17:00 Meta Back-Translation
Hieu Pham, Xinyi Wang, Yiming Yang, Graham Neubig
Poster
Wed 17:00 Conservative Safety Critics for Exploration
Homanga Bharadhwaj, Aviral Kumar, Nicholas Rhinehart, Sergey Levine, Florian Shkurti, Animesh Garg
Poster
Wed 17:00 Model-Based Visual Planning with Self-Supervised Functional Distances
Stephen Tian, Suraj Nair, Frederik Ebert, Sudeep Dasari, Ben Eysenbach, Chelsea Finn, Sergey Levine
Poster
Wed 17:00 Simple Augmentation Goes a Long Way: ADRL for DNN Quantization
Lin Ning, Guoyang Chen, Weifeng Zhang, Xipeng Shen
Poster
Wed 17:00 Adaptive Procedural Task Generation for Hard-Exploration Problems
Kuan Fang, Yuke Zhu, Silvio Savarese, Li Fei-Fei
Poster
Wed 17:00 Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling
Benedikt Boecking, Willie Neiswanger, Eric P Xing, Artur Dubrawski
Spotlight
Wed 19:35 Emergent Symbols through Binding in External Memory
Taylor Webb, Ishan Sinha, Jonathan Cohen
Wed 20:00 ML and Language (#1)
Spotlight
Wed 20:10 Graph-Based Continual Learning
Binh Tang, David S Matteson
Spotlight
Wed 20:20 Understanding the role of importance weighting for deep learning
Da Xu, Yuting Ye, Chuanwei Ruan
Spotlight
Wed 20:40 Undistillable: Making A Nasty Teacher That CANNOT teach students
Haoyu Ma, Tianlong Chen, Ting-Kuei Hu, Chenyu You, Xiaohui Xie, Zhangyang Wang
Spotlight
Wed 20:50 CPT: Efficient Deep Neural Network Training via Cyclic Precision
Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan Lin
Spotlight
Wed 21:15 PlasticineLab: A Soft-Body Manipulation Benchmark with Differentiable Physics
Zhiao Huang, Yuanming Hu, Tao Du, Siyuan Zhou, Hao Su, Joshua B Tenenbaum, Chuang Gan
Spotlight
Wed 21:25 Regularization Matters in Policy Optimization - An Empirical Study on Continuous Control
Zhuang Liu, Xuanlin Li, Bingyi Kang, trevor darrell
Spotlight
Wed 21:35 Regularized Inverse Reinforcement Learning
Wonseok Jeon, Chen-Yang Su, Paul Barde, Thang Doan, Derek Nowrouzezahrai, Joelle Pineau
Spotlight
Wed 21:45 Behavioral Cloning from Noisy Demonstrations
Fumihiro Sasaki, Ryota Yamashina
Oral
Thu 0:30 Optimal Rates for Averaged Stochastic Gradient Descent under Neural Tangent Kernel Regime
Atsushi Nitanda, Taiji Suzuki
Spotlight
Thu 0:45 Beyond Fully-Connected Layers with Quaternions: Parameterization of Hypercomplex Multiplications with $1/n$ Parameters
Aston Zhang, Yi Tay, Shuai Zhang, Alvin Chan, Anh Tuan Luu, Siu Hui, Jie Fu
Poster
Thu 1:00 Impact of Representation Learning in Linear Bandits
Jiaqi Yang, Wei Hu, Jason Lee, Simon Du
Poster
Thu 1:00 Grounding Language to Autonomously-Acquired Skills via Goal Generation
Ahmed Akakzia, Cédric Colas, Pierre-Yves Oudeyer, Mohamed CHETOUANI, Olivier Sigaud
Poster
Thu 1:00 Adaptive and Generative Zero-Shot Learning
Yu-Ying Chou, Hsuan-Tien (Tien) Lin, Tyng-Luh Liu
Poster
Thu 1:00 Contrastive Divergence Learning is a Time Reversal Adversarial Game
Omer Yair, Tomer Michaeli
Poster
Thu 1:00 Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models
Justin Bayer, Maximilian Soelch, Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt
Poster
Thu 1:00 Do not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning
Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu
Poster
Thu 1:00 Loss Function Discovery for Object Detection via Convergence-Simulation Driven Search
Peidong Liu, Gengwei Zhang, Bochao Wang, Hang Xu, Xiaodan Liang, Yong Jiang, Zhenguo Li
Poster
Thu 1:00 Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction
Wonkwang Lee, Whie Jung, Han Zhang, Ting Chen, Jing Yu Koh, Thomas E Huang, Hyungsuk Yoon, Honglak Lee, Seunghoon Hong
Poster
Thu 1:00 Learning Reasoning Paths over Semantic Graphs for Video-grounded Dialogues
(Henry) Hung Le, Nancy F Chen, Steven Hoi
Poster
Thu 1:00 Balancing Constraints and Rewards with Meta-Gradient D4PG
Dan A. Calian, Daniel J Mankowitz, Tom Zahavy, Zhongwen Xu, Junhyuk Oh, Nir Levine, Timothy A Mann
Poster
Thu 1:00 Adversarially Guided Actor-Critic
Yannis Flet-Berliac, Johan Ferret, Olivier Pietquin, philippe preux, Matthieu Geist
Poster
Thu 1:00 Go with the flow: Adaptive control for Neural ODEs
Mathieu Chalvidal, Matthew Ricci, Rufin VanRullen, Thomas Serre
Poster
Thu 1:00 Learning continuous-time PDEs from sparse data with graph neural networks
Valerii Iakovlev, Markus Heinonen, Harri Lähdesmäki
Poster
Thu 1:00 A Diffusion Theory For Deep Learning Dynamics: Stochastic Gradient Descent Exponentially Favors Flat Minima
Zeke Xie, Issei Sato, Masashi Sugiyama
Poster
Thu 1:00 Genetic Soft Updates for Policy Evolution in Deep Reinforcement Learning
Enrico Marchesini, Davide Corsi, Alessandro Farinelli
Poster
Thu 1:00 GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding
Dmitry Lepikhin, HyoukJoong Lee, Yuanzhong Xu, Dehao Chen, Orhan Firat, Yanping Huang, Maxim Krikun, Noam Shazeer, Zhifeng Chen
Poster
Thu 1:00 Conditional Generative Modeling via Learning the Latent Space
Sameera Ramasinghe, Kanchana Ranasinghe, Salman Khan, Nick Barnes, Stephen Gould
Poster
Thu 1:00 Practical Massively Parallel Monte-Carlo Tree Search Applied to Molecular Design
Xiufeng Yang, Tanuj Aasawat, Kazuki Yoshizoe
Poster
Thu 1:00 AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights
Byeongho Heo, Sanghyuk Chun, Seong Joon Oh, Dongyoon Han, Sangdoo Yun, Gyuwan Kim, Youngjung Uh, Jung-Woo Ha
Poster
Thu 1:00 Contrastive Learning with Adversarial Perturbations for Conditional Text Generation
Seanie Lee, Dong Bok Lee, Sung Ju Hwang
Poster
Thu 1:00 Latent Convergent Cross Mapping
Edward De Brouwer, Adam Arany, Jaak Simm, Yves Moreau
Poster
Thu 1:00 R-GAP: Recursive Gradient Attack on Privacy
Junyi Zhu, Matthew Blaschko
Poster
Thu 1:00 An Unsupervised Deep Learning Approach for Real-World Image Denoising
Dihan Zheng, Sia Huat Tan, Xiaowen Zhang, Zuoqiang Shi, Kaisheng Ma, Chenglong Bao
Poster
Thu 1:00 What Matters for On-Policy Deep Actor-Critic Methods? A Large-Scale Study
Marcin Andrychowicz, Anton Raichuk, Piotr Stanczyk, Manu Orsini, Sertan Girgin, Raphaël Marinier, Hussenot Hussenot-Desenonges, Matthieu Geist, Olivier Pietquin, Marcin Michalski, Sylvain Gelly, Olivier Bachem
Poster
Thu 1:00 Learning Neural Generative Dynamics for Molecular Conformation Generation
Minkai Xu, Shitong Luo, Yoshua Bengio, Jian Peng, Jian Tang
Poster
Thu 1:00 Hopfield Networks is All You Need
Hubert Ramsauer, Bernhard Schäfl, Johannes Lehner, Philipp Seidl, Michael Widrich, Lukas Gruber, Markus Holzleitner, Thomas Adler, David Kreil, Michael K Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter
Poster
Thu 1:00 Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes
Mike Gartrell, Insu Han, Elvis Dohmatob, Jennifer Gillenwater, Victor-Emmanuel Brunel
Poster
Thu 1:00 IOT: Instance-wise Layer Reordering for Transformer Structures
Jinhua Zhu, Lijun Wu, Yingce Xia, Shufang Xie, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu
Poster
Thu 1:00 Influence Estimation for Generative Adversarial Networks
Naoyuki Terashita, Hiroki Ohashi, Yuichi Nonaka, Takashi Kanemaru
Poster
Thu 1:00 Contrastive Explanations for Reinforcement Learning via Embedded Self Predictions
Zhengxian Lin, Kin-Ho Lam, Alan Fern
Poster
Thu 1:00 Repurposing Pretrained Models for Robust Out-of-domain Few-Shot Learning
Namyeong Kwon, Hwidong Na, Gabriel Huang, Simon Lacoste-Julien
Poster
Thu 1:00 Incremental few-shot learning via vector quantization in deep embedded space
Kuilin Chen, Chi-Guhn Lee
Poster
Thu 1:00 Kanerva++: Extending the Kanerva Machine With Differentiable, Locally Block Allocated Latent Memory
Jason Ramapuram, Yan Wu, Alexandros Kalousis
Poster
Thu 1:00 Learnable Embedding sizes for Recommender Systems
Siyi Liu, Chen Gao, Yihong Chen, Depeng Jin, Yong Li
Poster
Thu 1:00 Private Image Reconstruction from System Side Channels Using Generative Models
Yuanyuan Yuan, Shuai Wang, Junping Zhang
Poster
Thu 1:00 Learning What To Do by Simulating the Past
David Lindner, Rohin Shah, Pieter Abbeel, Anca Dragan
Poster
Thu 1:00 Free Lunch for Few-shot Learning: Distribution Calibration
Shuo Yang, Lu Liu, Min Xu
Poster
Thu 1:00 Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks
Yanbang Wang, Yen-Yu Chang, Yunyu Liu, Jure Leskovec, Pan Li
Poster
Thu 1:00 ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations
Rishabh Tiwari, Udbhav Bamba, Arnav Chavan, Deepak Gupta
Poster
Thu 1:00 Optimal Rates for Averaged Stochastic Gradient Descent under Neural Tangent Kernel Regime
Atsushi Nitanda, Taiji Suzuki
Poster
Thu 1:00 Continual learning in recurrent neural networks
Benjamin Ehret, Christian Henning, Maria Cervera, Alexander Meulemans, Johannes von Oswald, Benjamin F Grewe
Poster
Thu 1:00 Representation Balancing Offline Model-based Reinforcement Learning
Byung-Jun Lee, Jongmin Lee, Kee-Eung Kim
Poster
Thu 1:00 Learning Deep Features in Instrumental Variable Regression
Liyuan Xu, Yutian Chen, Siddarth Srinivasan, Nando de Freitas, Arnaud Doucet, Arthur Gretton
Poster
Thu 1:00 Network Pruning That Matters: A Case Study on Retraining Variants
Duong Le, Binh-Son Hua
Poster
Thu 1:00 CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning
Ossama Ahmed, Frederik Träuble, Anirudh Goyal, Alexander Neitz, Manuel Wuthrich, Yoshua Bengio, Bernhard Schoelkopf, Stefan Bauer
Poster
Thu 1:00 Counterfactual Generative Networks
Axel Sauer, Andreas Geiger
Oral
Thu 3:00 What Matters for On-Policy Deep Actor-Critic Methods? A Large-Scale Study
Marcin Andrychowicz, Anton Raichuk, Piotr Stanczyk, Manu Orsini, Sertan Girgin, Raphaël Marinier, Hussenot Hussenot-Desenonges, Matthieu Geist, Olivier Pietquin, Marcin Michalski, Sylvain Gelly, Olivier Bachem
Spotlight
Thu 3:15 Winning the L2RPN Challenge: Power Grid Management via Semi-Markov Afterstate Actor-Critic
Deunsol Yoon, Sunghoon Hong, Byung-Jun Lee, Kee-Eung Kim
Spotlight
Thu 3:25 UPDeT: Universal Multi-agent RL via Policy Decoupling with Transformers
Siyi Hu, Fengda Zhu, Xiaojun Chang, Xiaodan Liang
Spotlight
Thu 3:35 Quantifying Differences in Reward Functions
Adam Gleave, Michael Dennis, Shane Legg, Stuart Russell, Jan Leike
Spotlight
Thu 3:45 Iterative Empirical Game Solving via Single Policy Best Response
Max Smith, Thomas Anthony, Michael Wellman
Spotlight
Thu 3:55 Discovering a set of policies for the worst case reward
Tom Zahavy, Andre Barreto, Daniel J Mankowitz, Shaobo Hou, Brendan ODonoghue, Iurii Kemaev, Satinder Singh
Oral
Thu 4:20 Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
Yuan Yin, Vincent Le Guen, Jérémie DONA, Emmanuel d Bezenac, Ibrahim Ayed, Nicolas THOME, patrick gallinari
Spotlight
Thu 4:35 Unlearnable Examples: Making Personal Data Unexploitable
Hanxun Huang, Daniel Ma, Sarah Erfani, James Bailey, Yisen Wang
Spotlight
Thu 4:45 Self-supervised Visual Reinforcement Learning with Object-centric Representations
Andrii Zadaianchuk, Maximilian Seitzer, Georg Martius
Spotlight
Thu 4:55 On Self-Supervised Image Representations for GAN Evaluation
Stanislav Morozov, Andrey Voynov, Artem Babenko
Spotlight
Thu 5:15 Practical Real Time Recurrent Learning with a Sparse Approximation
Jacob Menick, Erich Elsen, Utku Evci, Simon Osindero, Karen Simonyan, Alex Graves
Poster
Thu 9:00 Rethinking Soft Labels for Knowledge Distillation: A Bias–Variance Tradeoff Perspective
Helong Zhou, Liangchen Song, Jiajie Chen, Ye Zhou, Guoli Wang, Junsong Yuan, Qian Zhang
Poster
Thu 9:00 Deep Networks and the Multiple Manifold Problem
Sam Buchanan, Dar Gilboa, John Wright
Poster
Thu 9:00 Dynamic Tensor Rematerialization
Marisa Kirisame, Steven S. Lyubomirsky, Altan Haan, Jennifer Brennan, Mike He, Jared G Roesch, Tianqi Chen, Zachary Tatlock
Poster
Thu 9:00 Gradient Vaccine: Investigating and Improving Multi-task Optimization in Massively Multilingual Models
Zirui Wang, Yulia Tsvetkov, Orhan Firat, Yuan Cao
Poster
Thu 9:00 Variational Information Bottleneck for Effective Low-Resource Fine-Tuning
Rabeeh Karimi Mahabadi, Yonatan Belinkov, James Henderson
Poster
Thu 9:00 C-Learning: Learning to Achieve Goals via Recursive Classification
Ben Eysenbach, Ruslan Salakhutdinov, Sergey Levine
Poster
Thu 9:00 EEC: Learning to Encode and Regenerate Images for Continual Learning
Ali Ayub, Alan Wagner
Poster
Thu 9:00 Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning
Rishabh Agarwal, Marlos C. Machado, Pablo Samuel Castro, Marc G Bellemare
Poster
Thu 9:00 Integrating Categorical Semantics into Unsupervised Domain Translation
Samuel Lavoie, Faruk Ahmed, Aaron Courville
Poster
Thu 9:00 Graph Coarsening with Neural Networks
Chen Cai, Dingkang Wang, Yusu Wang
Poster
Thu 9:00 Learning to Recombine and Resample Data For Compositional Generalization
Ekin Akyürek, Afra Feyza Akyürek, Jacob Andreas
Poster
Thu 9:00 A Critique of Self-Expressive Deep Subspace Clustering
Ben Haeffele, Chong You, Rene Vidal
Poster
Thu 9:00 Efficient Transformers in Reinforcement Learning using Actor-Learner Distillation
Emilio Parisotto, Ruslan Salakhutdinov
Poster
Thu 9:00 Lifelong Learning of Compositional Structures
Jorge Mendez, ERIC EATON
Poster
Thu 9:00 End-to-end Adversarial Text-to-Speech
Jeff Donahue, Sander Dieleman, Mikolaj Binkowski, Erich Elsen, Karen Simonyan
Poster
Thu 9:00 Dataset Condensation with Gradient Matching
Bo ZHAO, Konda Reddy Mopuri, Hakan Bilen
Poster
Thu 9:00 CaPC Learning: Confidential and Private Collaborative Learning
Christopher Choquette-Choo, Natalie Dullerud, Adam Dziedzic, Yunxiang Zhang, Somesh Jha, Nicolas Papernot, Xiao Wang
Poster
Thu 9:00 Heating up decision boundaries: isocapacitory saturation, adversarial scenarios and generalization bounds
Bogdan Georgiev, Lukas Franken, Mayukh Mukherjee
Poster
Thu 9:00 Contrastive Learning with Hard Negative Samples
Joshua Robinson, Ching-Yao Chuang, Suvrit Sra, Stefanie Jegelka
Poster
Thu 9:00 Hierarchical Reinforcement Learning by Discovering Intrinsic Options
Jesse Zhang, Haonan Yu, Wei Xu
Poster
Thu 9:00 Learning to Set Waypoints for Audio-Visual Navigation
Changan Chen, Sagnik Majumder, Ziad Al-Halah, Ruohan Gao, Santhosh Kumar Ramakrishnan, Kristen Grauman