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 ]

315 Results

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 Progressive Skeletonization: Trimming more fat from a network at initialization
Pau de Jorge Aranda, Amartya Sanyal, Harkirat Singh Behl, Philip Torr, Grégory Rogez, Puneet Dokania
Poster
Mon 1:00 Towards Robust Neural Networks via Close-loop Control
Zhuotong Chen, Qianxiao Li, Zheng 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 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 Training with Quantization Noise for Extreme Model Compression
Pierre Stock, Angela Fan, Benjamin Graham, Edouard Grave, Rémi Gribonval, Hervé Jégou, Armand Joulin
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 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 Meta-GMVAE: Mixture of Gaussian VAE for Unsupervised Meta-Learning
Dong Bok Lee, Dongchan Min, Seanie Lee, Sung Ju Hwang
Poster
Mon 1:00 PSTNet: Point Spatio-Temporal Convolution on Point Cloud Sequences
Hehe Fan, Xin Yu, Yuhang Ding, Yi Yang, Mohan Kankanhalli
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 Neural Jump Ordinary Differential Equations: Consistent Continuous-Time Prediction and Filtering
Calypso Herrera, Florian Krach, Josef Teichmann
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 Towards Robustness Against Natural Language Word Substitutions
Xinshuai Dong, Anh Tuan Luu, Rongrong Ji, Hong Liu
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 Deciphering and Optimizing Multi-Task Learning: a Random Matrix Approach
Malik Tiomoko, Hafiz Tiomoko Ali, Romain Couillet
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
Spotlight
Mon 3:30 Deciphering and Optimizing Multi-Task Learning: a Random Matrix Approach
Malik Tiomoko, Hafiz Tiomoko Ali, Romain Couillet
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 5:45 Contrastive Divergence Learning is a Time Reversal Adversarial Game
Omer Yair, Tomer Michaeli
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 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 MultiModalQA: complex question answering over text, tables and images
Alon Talmor, Ori Yoran, Amnon Catav, Dan Lahav, Yizhong Wang, Akari Asai, Gabriel Ilharco, Hannaneh Hajishirzi, Jonathan Berant
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 On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines
Marius Mosbach, Maksym Andriushchenko, Dietrich Klakow
Poster
Mon 9:00 Predicting Classification Accuracy When Adding New Unobserved Classes
Yuli Slavutsky, Yuval Benjamini
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 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 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 GraPPa: Grammar-Augmented Pre-Training for Table Semantic Parsing
Tao Yu, Jason Wu, Xi V Lin, bailin wang, Yi Tan, Xinyi Yang, Dragomir Radev, Richard Socher, Caiming Xiong
Poster
Mon 9:00 LiftPool: Bidirectional ConvNet Pooling
Jiaojiao Zhao, Cees G Snoek
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 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 Revisiting Few-sample BERT Fine-tuning
Tianyi Zhang, Felix Wu, Arzoo Katiyar, Kilian Weinberger, Yoav Artzi
Poster
Mon 9:00 Overparameterisation and worst-case generalisation: friend or foe?
Aditya Krishna Menon, Ankit Singh Rawat, Sanjiv Kumar
Poster
Mon 9:00 Predicting Inductive Biases of Pre-Trained Models
Charles Lovering, Rohan Jha, Tal Linzen, Ellie Pavlick
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 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 The Traveling Observer Model: Multi-task Learning Through Spatial Variable Embeddings
Elliot Meyerson, Risto Miikkulainen
Poster
Mon 9:00 Learning with AMIGo: Adversarially Motivated Intrinsic Goals
Andres Campero, Roberta Raileanu, Heinrich Kuttler, Joshua B Tenenbaum, Tim Rocktaeschel, Ed Grefenstette
Spotlight
Mon 11:45 Geometry-Aware Gradient Algorithms for Neural Architecture Search
Liam Li, Misha Khodak, Nina Balcan, Ameet Talwalkar
Mon 12:00 Operationalizing AI for Healthcare
Spotlight
Mon 12:25 Sharpness-aware Minimization for Efficiently Improving Generalization
Pierre Foret, Ariel Kleiner, Hossein Mobahi, Behnam Neyshabur
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 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
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 Robust Reinforcement Learning on State Observations with Learned Optimal Adversary
Huan Zhang, Hongge Chen, Duane S Boning, Cho-Jui Hsieh
Poster
Mon 17:00 Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks
Yige Li, Xixiang Lyu, Nodens Koren, Lingjuan Lyu, Bo Li, Daniel Ma
Poster
Mon 17:00 Rethinking Positional Encoding in Language Pre-training
Guolin Ke, Di He, Tie-Yan Liu
Poster
Mon 17:00 Taking Notes on the Fly Helps Language Pre-Training
Qiyu Wu, Chen Xing, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu
Poster
Mon 17:00 Bypassing the Ambient Dimension: Private SGD with Gradient Subspace Identification
Yingxue Zhou, Steven Wu, Arindam Banerjee
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 SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness
Mikhail Yurochkin, Yuekai Sun
Poster
Mon 17:00 Explaining the Efficacy of Counterfactually Augmented Data
Divyansh Kaushik, Amrith Setlur, Eduard H Hovy, Zachary Lipton
Poster
Mon 17:00 Proximal Gradient Descent-Ascent: Variable Convergence under KŁ Geometry
Ziyi Chen, Yi Zhou, Tengyu Xu, Yingbin Liang
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 Offline Model-Based Optimization via Normalized Maximum Likelihood Estimation
Justin Fu, Sergey Levine
Poster
Mon 17:00 Regularized Inverse Reinforcement Learning
Wonseok Jeon, Chen-Yang Su, Paul Barde, Thang Doan, Derek Nowrouzezahrai, Joelle Pineau
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 SCoRe: Pre-Training for Context Representation in Conversational Semantic Parsing
Tao Yu, Rui Zhang, Alex Polozov, Christopher Meek, Ahmed H Awadallah
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 Decentralized Attribution of Generative Models
Changhoon Kim, Yi Ren, 'YZ' Yezhou Yang
Poster
Mon 17:00 Deberta: Decoding-Enhanced Bert With Disentangled Attention
Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen
Poster
Mon 17:00 Rethinking Architecture Selection in Differentiable NAS
Ruochen Wang, Minhao Cheng, Xiangning Chen, Xiaocheng Tang, Cho-Jui Hsieh
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 Score-Based Generative Modeling through Stochastic Differential Equations
Yang Song, Jascha Sohl-Dickstein, Durk Kingma, Abhishek Kumar, Stefano Ermon, Ben Poole
Poster
Mon 17:00 Learning Energy-Based Models by Diffusion Recovery Likelihood
Ruiqi Gao, Yang Song, Ben Poole, Yingnian Wu, Durk Kingma
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 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 20:28 Fast Geometric Projections for Local Robustness Certification
Aymeric Fromherz, Klas Leino, Matt Fredrikson, Bryan Parno, Corina Pasareanu
Spotlight
Mon 20:48 Dataset Inference: Ownership Resolution in Machine Learning
Pratyush Maini, Mohammad Yaghini, Nicolas Papernot
Spotlight
Mon 20:58 HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark
Chaojian Li, Zhongzhi Yu, Yonggan Fu, Yongan Zhang, Yang Zhao, Haoran You, Qixuan Yu, Yue Wang, Cong Hao, Yingyan Lin
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 Efficient Certified Defenses Against Patch Attacks on Image Classifiers
Jan Hendrik Metzen, Maksym Yatsura
Poster
Tue 1:00 Improving Transformation Invariance in Contrastive Representation Learning
Adam Foster, Rattana Pukdee, 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 A Universal Representation Transformer Layer for Few-Shot Image Classification
Lu Liu, Will Hamilton, Guodong Long, Jing Jiang, Hugo Larochelle
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 Group Equivariant Conditional Neural Processes
Makoto Kawano, Wataru Kumagai, Akiyoshi Sannai, Yusuke Iwasawa, Yutaka Matsuo
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 Learning the Pareto Front with Hypernetworks
Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik
Poster
Tue 1:00 GraphCodeBERT: Pre-training Code Representations with Data Flow
Daya Guo, Shuo Ren, Shuai Lu, Zhangyin Feng, Duyu Tang, Shujie LIU, Long Zhou, Nan Duan, Alexey Svyatkovskiy, Shengyu Fu, Michele Tufano, Shao Kun Deng, Colin Clement, Dawn Drain, Neels Sundaresan, Jian Yin, Daxin Jiang, Ming Zhou
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 not-MIWAE: Deep Generative Modelling with Missing not at Random Data
Niels Ipsen, Pierre-Alexandre Mattei, Jes Frellsen
Poster
Tue 1:00 Exemplary Natural Images Explain CNN Activations Better than State-of-the-Art Feature Visualization
Judy Borowski, Roland Zimmermann, Judith Schepers, Robert Geirhos, Thomas S Wallis, Matthias Bethge, Wieland Brendel
Poster
Tue 1:00 Bayesian Context Aggregation for Neural Processes
Michael Volpp, Fabian Flürenbrock, Lukas Grossberger, Christian Daniel, Gerhard Neumann
Poster
Tue 1:00 Sample-Efficient Automated Deep Reinforcement Learning
Jörg Franke, Gregor Koehler, André Biedenkapp, Frank Hutter
Poster
Tue 1:00 SkipW: Resource Adaptable RNN with Strict Upper Computational Limit
Tsiry MAYET, Anne Lambert, Pascal Le Guyadec, Francoise Le Bolzer, François Schnitzler
Poster
Tue 1:00 Refining Deep Generative Models via Discriminator Gradient Flow
Abdul Fatir Ansari, Ming Liang Ang, Harold Soh
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
Tue 5:00 Effect of demographic makeup in covid vaccine administration
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 Quantifying Differences in Reward Functions
Adam Gleave, Michael Dennis, Shane Legg, Stuart Russell, Jan Leike
Poster
Tue 9:00 Teaching with Commentaries
Aniruddh Raghu, Maithra Raghu, Simon Kornblith, David Duvenaud, Geoffrey Hinton
Poster
Tue 9:00 The geometry of integration in text classification RNNs
Kyle Aitken, Vinay Ramasesh, Ankush Garg, Yuan Cao, David Sussillo, Niru Maheswaranathan
Poster
Tue 9:00 Meta-learning Symmetries by Reparameterization
Allan Zhou, Tom Knowles, Chelsea Finn
Poster
Tue 9:00 Auction Learning as a Two-Player Game
Jad Rahme, Samy Jelassi, S. M Weinberg
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 FairBatch: Batch Selection for Model Fairness
Yuji Roh, Kangwook Lee, Steven Whang, Changho Suh
Poster
Tue 9:00 Vulnerability-Aware Poisoning Mechanism for Online RL with Unknown Dynamics
Yanchao Sun, Da Huo, Furong Huang
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 Physics-aware, probabilistic model order reduction with guaranteed stability
Sebastian Kaltenbach, PS Koutsourelakis
Poster
Tue 9:00 Learning Neural Event Functions for Ordinary Differential Equations
Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel
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 Learning Robust State Abstractions for Hidden-Parameter Block MDPs
Amy Zhang, Shagun Sodhani, Khimya Khetarpal, Joelle Pineau
Poster
Tue 9:00 DC3: A learning method for optimization with hard constraints
Priya Donti, David Rolnick, Zico Kolter
Poster
Tue 9:00 Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding
Sana Tonekaboni, Danny Eytan, Anna Goldenberg
Poster
Tue 9:00 Robust Pruning at Initialization
Soufiane Hayou, Jean-Francois Ton, Arnaud Doucet, Yee Whye Teh
Poster
Tue 9:00 Self-Supervised Learning of Compressed Video Representations
Youngjae Yu, Sangho Lee, Gunhee Kim, Yale Song
Poster
Tue 9:00 Statistical inference for individual fairness
Subha Maity, Songkai Xue, Mikhail Yurochkin, Yuekai Sun
Poster
Tue 9:00 UMEC: Unified model and embedding compression for efficient recommendation systems
Jiayi Shen, Haotao Wang, Shupeng Gui, Jianchao Tan, Zhangyang Wang, Ji Liu
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 Provable Rich Observation Reinforcement Learning with Combinatorial Latent States
Dipendra Misra, Qinghua Liu, Chi Jin, John Langford
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 DINO: A Conditional Energy-Based GAN for Domain Translation
Konstantinos Vougioukas, Stavros Petridis, Maja Pantic
Poster
Tue 9:00 Global optimality of softmax policy gradient with single hidden layer neural networks in the mean-field regime
Andrea Agazzi, Jianfeng Lu
Poster
Tue 9:00 Mapping the Timescale Organization of Neural Language Models
Hsiang-Yun Sherry Chien, Jinhan Zhang, Christopher Honey
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 Knowledge Distillation as Semiparametric Inference
Tri Dao, Govinda Kamath, Vasilis Syrgkanis, Lester Mackey
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 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
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 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 Usable Information and Evolution of Optimal Representations During Training
Michael Kleinman, Alessandro Achille, Daksh Idnani, Jonathan Kao
Poster
Tue 17:00 DDPNOpt: Differential Dynamic Programming Neural Optimizer
Guan-Horng Liu, Tianrong Chen, Evangelos Theodorou
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 Dataset Inference: Ownership Resolution in Machine Learning
Pratyush Maini, Mohammad Yaghini, Nicolas Papernot
Poster
Tue 17:00 Individually Fair Rankings
Amanda Bower, Hamid Eftekhari, Mikhail Yurochkin, Yuekai Sun
Poster
Tue 17:00 Diverse Video Generation using a Gaussian Process Trigger
Gaurav Shrivastava, Abhinav Shrivastava
Poster
Tue 17:00 Denoising Diffusion Implicit Models
Jiaming Song, Chenlin Meng, Stefano Ermon
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 Understanding the role of importance weighting for deep learning
Da Xu, Yuting Ye, Chuanwei Ruan
Poster
Tue 17:00 Contextual Dropout: An Efficient Sample-Dependent Dropout Module
XINJIE FAN, Shujian Zhang, Korawat Tanwisuth, Xiaoning Qian, Mingyuan Zhou
Spotlight
Tue 19:15 DDPNOpt: Differential Dynamic Programming Neural Optimizer
Guan-Horng Liu, Tianrong Chen, Evangelos Theodorou
Spotlight
Tue 19:25 Orthogonalizing Convolutional Layers with the Cayley Transform
Asher Trockman, Zico Kolter
Spotlight
Tue 20:20 Async-RED: A Provably Convergent Asynchronous Block Parallel Stochastic Method using Deep Denoising Priors
Yu Sun, Jiaming Liu, Yiran Sun, Brendt Wohlberg, Ulugbek Kamilov
Spotlight
Tue 20:30 Individually Fair Gradient Boosting
Alexander Vargo, Fan Zhang, Mikhail Yurochkin, Yuekai Sun
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 Acting in Delayed Environments with Non-Stationary Markov Policies
Esther Derman, Gal Dalal, Shie Mannor
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 Neural ODE Processes
Alexander Norcliffe, Cristian Bodnar, Ben Day, Jacob Moss, Pietro Liò
Poster
Wed 1:00 Deep Neural Network Fingerprinting by Conferrable Adversarial Examples
Nils Lukas, Yuxuan Zhang, Florian Kerschbaum
Poster
Wed 1:00 Byzantine-Resilient Non-Convex Stochastic Gradient Descent
Zeyuan Allen-Zhu, Faeze Ebrahimianghazani, Jerry Li, Dan Alistarh
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 Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels
Binxin Ru, Xingchen Wan, Xiaowen Dong, Michael Osborne
Poster
Wed 1:00 An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, Neil Houlsby
Poster
Wed 1:00 Bag of Tricks for Adversarial Training
Tianyu Pang, Xiao Yang, Yinpeng Dong, Hang Su, Jun Zhu
Poster
Wed 1:00 Deep Learning meets Projective Clustering
Alaa Maalouf, Harry Lang, Daniela Rus, Dan Feldman
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 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 Auxiliary Task Update Decomposition: The Good, the Bad and the Neutral
Lucio Dery, Yann Dauphin, David Grangier
Poster
Wed 1:00 Identifying Physical Law of Hamiltonian Systems via Meta-Learning
Seungjun Lee, Haesang Yang, Woojae Seong
Poster
Wed 1:00 Net-DNF: Effective Deep Modeling of Tabular Data
Liran Katzir, Gal Elidan, Ran El-Yaniv
Oral
Wed 3:00 An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, Neil Houlsby
Spotlight
Wed 4:40 Deep Neural Network Fingerprinting by Conferrable Adversarial Examples
Nils Lukas, Yuxuan Zhang, Florian Kerschbaum
Spotlight
Wed 5:35 Neural Approximate Sufficient Statistics for Implicit Models
Yanzhi Chen, Dinghuai Zhang, Michael U Gutmann, Aaron Courville, Zhanxing Zhu
Poster
Wed 9:00 Anytime Sampling for Autoregressive Models via Ordered Autoencoding
Yilun Xu, Yang Song, Sahaj Garg, Linyuan Gong, Rui Shu, Aditya Grover, Stefano Ermon
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 Neural Synthesis of Binaural Speech From Mono Audio
Alexander Richard, Dejan Markovic, Israel Gebru, Steven Krenn, Gladstone A Butler, Fernando Torre, Yaser Sheikh
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 Probabilistic Numeric Convolutional Neural Networks
Marc Finzi, Roberto Bondesan, Max Welling
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 Sharpness-aware Minimization for Efficiently Improving Generalization
Pierre Foret, Ariel Kleiner, Hossein Mobahi, Behnam Neyshabur
Poster
Wed 9:00 Property Controllable Variational Autoencoder via Invertible Mutual Dependence
Xiaojie Guo, Yuanqi Du, Liang Zhao
Poster
Wed 9:00 For self-supervised learning, Rationality implies generalization, provably
Yamini Bansal, Gal Kaplun, Boaz Barak
Poster
Wed 9:00 Modeling the Second Player in Distributionally Robust Optimization
Paul Michel, Tatsunori Hashimoto, Graham Neubig
Poster
Wed 9:00 NAS-Bench-ASR: Reproducible Neural Architecture Search for Speech Recognition
Abhinav Mehrotra, Alberto Gil Couto Pimentel Ramos, Sourav Bhattacharya, Łukasz Dudziak, Ravichander Vipperla, Thomas C Chau, Mohamed Abdelfattah, Samin Ishtiaq, Nic Lane
Poster
Wed 9:00 Geometry-Aware Gradient Algorithms for Neural Architecture Search
Liam Li, Misha Khodak, Nina Balcan, Ameet Talwalkar
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 Few-Shot Bayesian Optimization with Deep Kernel Surrogates
Martin Wistuba, Josif Grabocka
Poster
Wed 9:00 Orthogonalizing Convolutional Layers with the Cayley Transform
Asher Trockman, Zico Kolter
Poster
Wed 9:00 Learning Task-General Representations with Generative Neuro-Symbolic Modeling
Reuben Feinman, Brenden Lake
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
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 12:23 Coupled Oscillatory Recurrent Neural Network (coRNN): An accurate and (gradient) stable architecture for learning long time dependencies
T. Konstantin Rusch, Siddhartha Mishra
Oral
Wed 16:00 Neural Synthesis of Binaural Speech From Mono Audio
Alexander Richard, Dejan Markovic, Israel Gebru, Steven Krenn, Gladstone A Butler, Fernando Torre, Yaser Sheikh
Oral
Wed 16:30 Score-Based Generative Modeling through Stochastic Differential Equations
Yang Song, Jascha Sohl-Dickstein, Durk Kingma, Abhishek Kumar, Stefano Ermon, Ben Poole
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 Improved Autoregressive Modeling with Distribution Smoothing
Chenlin Meng, Jiaming Song, Yang Song, Shengjia Zhao, Stefano Ermon
Poster
Wed 17:00 Individually Fair Gradient Boosting
Alexander Vargo, Fan Zhang, Mikhail Yurochkin, Yuekai Sun
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 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 Filtered Inner Product Projection for Crosslingual Embedding Alignment
Vin Sachidananda, Ziyi Yang, Chenguang Zhu
Poster
Wed 17:00 Efficient Wasserstein Natural Gradients for Reinforcement Learning
Ted Moskovitz, Michael Arbel, Ferenc Huszar, Arthur Gretton
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 Effective and Efficient Vote Attack on Capsule Networks
Jindong Gu, Baoyuan Wu, Volker Tresp
Poster
Wed 17:00 Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling
Benedikt Boecking, Willie Neiswanger, Eric P Xing, Artur Dubrawski
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 Deep Encoder, Shallow Decoder: Reevaluating Non-autoregressive Machine Translation
Jungo Kasai, Nikolaos Pappas, Hao Peng, James Cross, Noah Smith
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 Adaptive Universal Generalized PageRank Graph Neural Network
Eli Chien, Jianhao Peng, Pan Li, Olgica Milenkovic
Poster
Wed 17:00 Efficient Conformal Prediction via Cascaded Inference with Expanded Admission
Adam Fisch, Tal Schuster, Tommi Jaakkola, Regina Barzilay
Poster
Wed 17:00 Emergent Symbols through Binding in External Memory
Taylor Webb, Ishan Sinha, Jonathan Cohen
Poster
Wed 17:00 Efficient Reinforcement Learning in Factored MDPs with Application to Constrained RL
Xiaoyu Chen, Jiachen Hu, Lihong Li, Liwei Wang
Oral
Wed 19:00 Improved Autoregressive Modeling with Distribution Smoothing
Chenlin Meng, Jiaming Song, Yang Song, Shengjia Zhao, Stefano Ermon
Spotlight
Wed 19:15 GAN "Steerability" without optimization
Nurit Spingarn Eliezer, Ron Banner, Tomer Michaeli
Spotlight
Wed 19:35 Emergent Symbols through Binding in External Memory
Taylor Webb, Ishan Sinha, Jonathan Cohen
Oral
Wed 19:55 Deformable DETR: Deformable Transformers for End-to-End Object Detection
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, Jifeng Dai
Spotlight
Wed 20:20 Understanding the role of importance weighting for deep learning
Da Xu, Yuting Ye, Chuanwei Ruan
Spotlight
Wed 20:30 Towards Robustness Against Natural Language Word Substitutions
Xinshuai Dong, Anh Tuan Luu, Rongrong Ji, Hong Liu
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 21:35 Regularized Inverse Reinforcement Learning
Wonseok Jeon, Chen-Yang Su, Paul Barde, Thang Doan, Derek Nowrouzezahrai, Joelle Pineau
Oral
Thu 0:00 Rethinking Architecture Selection in Differentiable NAS
Ruochen Wang, Minhao Cheng, Xiangning Chen, Xiaocheng Tang, Cho-Jui Hsieh
Poster
Thu 1:00 Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks
Shikuang Deng, Shi Gu
Poster
Thu 1:00 Efficient Inference of Flexible Interaction in Spiking-neuron Networks
Feng Zhou, Yixuan Zhang, Jun Zhu
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 Certify or Predict: Boosting Certified Robustness with Compositional Architectures
Mark Niklas Mueller, Mislav Balunovic, Martin Vechev
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 Deformable DETR: Deformable Transformers for End-to-End Object Detection
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, Jifeng Dai
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 Continual learning in recurrent neural networks
Benjamin Ehret, Christian Henning, Maria Cervera, Alexander Meulemans, Johannes von Oswald, Benjamin F Grewe
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 Colorization Transformer
Manoj Kumar, Dirk Weissenborn, Nal Kalchbrenner
Poster
Thu 1:00 R-GAP: Recursive Gradient Attack on Privacy
Junyi Zhu, Matthew Blaschko
Poster
Thu 1:00 Contrastive Divergence Learning is a Time Reversal Adversarial Game
Omer Yair, Tomer Michaeli
Poster
Thu 1:00 Understanding the effects of data parallelism and sparsity on neural network training
Namhoon Lee, Thalaiyasingam Ajanthan, Philip Torr, Martin Jaggi
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 ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations
Rishabh Tiwari, Udbhav Bamba, Arnav Chavan, Deepak Gupta
Poster
Thu 1:00 Distilling Knowledge from Reader to Retriever for Question Answering
Gautier Izacard, Edouard Grave
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 Latent Convergent Cross Mapping
Edward De Brouwer, Adam Arany, Jaak Simm, Yves Moreau
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 GAN "Steerability" without optimization
Nurit Spingarn Eliezer, Ron Banner, Tomer Michaeli
Poster
Thu 1:00 Private Image Reconstruction from System Side Channels Using Generative Models
Yuanyuan Yuan, Shuai Wang, Junping Zhang
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 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 Counterfactual Generative Networks
Axel Sauer, Andreas Geiger
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
Poster
Thu 9:00 Neural Spatio-Temporal Point Processes
Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel
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 Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning
Rishabh Agarwal, Marlos C. Machado, Pablo Samuel Castro, Marc G Bellemare
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 Heating up decision boundaries: isocapacitory saturation, adversarial scenarios and generalization bounds
Bogdan Georgiev, Lukas Franken, Mayukh Mukherjee
Poster
Thu 9:00 A Mathematical Exploration of Why Language Models Help Solve Downstream Tasks
Nikunj Saunshi, Sadhika Malladi, Sanjeev Arora
Poster
Thu 9:00 Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters & Less Data
Jonathan Pilault, Amine EL hattami, Chris J Pal
Poster
Thu 9:00 Cut out the annotator, keep the cutout: better segmentation with weak supervision
Sarah Hooper, Michael Wornow, Ying Seah, Peter Kellman, Hui Xue, Frederic Sala, Curtis Langlotz, Christopher Re
Poster
Thu 9:00 Adversarially-Trained Deep Nets Transfer Better: Illustration on Image Classification
Francisco Utrera, Evan Kravitz, N. Benjamin Erichson, Rajiv Khanna, Michael W Mahoney
Poster
Thu 9:00 BSQ: Exploring Bit-Level Sparsity for Mixed-Precision Neural Network Quantization
Huanrui Yang, Lin Duan, Yiran Chen, Hai Li
Poster
Thu 9:00 Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective
Muhammet Balcilar, Guillaume Renton, Pierre Héroux, Benoit Gaüzère, Sébastien Adam, Paul Honeine
Poster
Thu 9:00 Directed Acyclic Graph Neural Networks
Veronika Thost, Jie Chen
Poster
Thu 9:00 Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma Augmented Gaussian Processes
Jake Snell, Richard Zemel
Thu 9:00 Bad hypothesis contest
Oral
Thu 11:15 SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness
Mikhail Yurochkin, Yuekai Sun
Spotlight
Thu 12:20 Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning
Rishabh Agarwal, Marlos C. Machado, Pablo Samuel Castro, Marc G Bellemare
Poster
Thu 17:00 Fast Geometric Projections for Local Robustness Certification
Aymeric Fromherz, Klas Leino, Matt Fredrikson, Bryan Parno, Corina Pasareanu
Poster
Thu 17:00 Combining Label Propagation and Simple Models out-performs Graph Neural Networks
Qian Huang, Horace He, Abhay Singh, Ser-Nam Lim, Austin Benson
Poster
Thu 17:00 In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning
Mamshad Nayeem Rizve, Kevin Duarte, Yogesh S Rawat, Mubarak Shah
Poster
Thu 17:00 HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark
Chaojian Li, Zhongzhi Yu, Yonggan Fu, Yongan Zhang, Yang Zhao, Haoran You, Qixuan Yu, Yue Wang, Cong Hao, Yingyan Lin
Poster
Thu 17:00 Representing Partial Programs with Blended Abstract Semantics
Maxwell Nye, Yewen Pu, Matthew Bowers, Jacob Andreas, Joshua B Tenenbaum, Armando Solar-Lezama
Poster
Thu 17:00 Molecule Optimization by Explainable Evolution
Binghong Chen, Tianzhe Wang, Chengtao Li, Hanjun Dai, Le Song
Poster
Thu 17:00 LowKey: Leveraging Adversarial Attacks to Protect Social Media Users from Facial Recognition
Valeria Cherepanova, Micah Goldblum, Harrison Foley, Shiyuan Duan, John P Dickerson, Gavin Taylor, Tom Goldstein
Poster
Thu 17:00 Async-RED: A Provably Convergent Asynchronous Block Parallel Stochastic Method using Deep Denoising Priors
Yu Sun, Jiaming Liu, Yiran Sun, Brendt Wohlberg, Ulugbek Kamilov
Poster
Thu 17:00 Multi-Prize Lottery Ticket Hypothesis: Finding Accurate Binary Neural Networks by Pruning A Randomly Weighted Network
James Diffenderfer, Bhavya Kailkhura
Poster
Thu 17:00 Factorizing Declarative and Procedural Knowledge in Structured, Dynamical Environments
Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Charles Blundell, Sergey Levine, Yoshua Bengio, Mike Mozer
Poster
Thu 17:00 DynaTune: Dynamic Tensor Program Optimization in Deep Neural Network Compilation
Minjia Zhang, Menghao Li, Chi Wang, Mingqin Li
Poster
Thu 17:00 Learning Energy-Based Generative Models via Coarse-to-Fine Expanding and Sampling
Yang Zhao, Jianwen Xie, Ping Li
Poster
Thu 17:00 The Recurrent Neural Tangent Kernel
Sina Alemohammad, Jack Wang, Randall Balestriero, Richard Baraniuk
Poster
Thu 17:00 ARMOURED: Adversarially Robust MOdels using Unlabeled data by REgularizing Diversity
Kangkang Lu, Alfred Nguyen, Xun Xu, Kiran Chari, Yu Jing Goh, CS Foo
Poster
Thu 17:00 On the Curse of Memory in Recurrent Neural Networks: Approximation and Optimization Analysis
Zhong Li, Jiequn Han, Weinan E, Qianxiao Li
Poster
Thu 17:00 Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers
Kaidi Xu, Huan Zhang, Shiqi Wang, Yihan Wang, Suman Jana, Xue Lin, Cho-Jui Hsieh
Workshop
Fri 2:45 Ideas for machine learning from psychology's reproducibility crisis
Samuel J Bell
Workshop
Fri 4:45 Hardware-Aware Efficient Training of Deep Learning Models
Ghouthi BOUKLI HACENE, Vincent Gripon, François Leduc-Primeau, Vahid Partovi Nia, Fan Yang, Andreas Moshovos, Yoshua Bengio
Workshop
Fri 5:00 Geometric and Topological Representation Learning
Guy Wolf, Xiuyuan Cheng, Smita Krishnaswamy, Jure Leskovec, Bastian Rieck, Soledad Villar
Workshop
Fri 5:10 Hugo Larochelle, Google Brain Montréal, Adjunct Professor at Université de Montréal and a Canada CIFAR Chair
Hugo Larochelle
Workshop
Fri 5:15 Beyond Static Papers: Rethinking How We Share Scientific Understanding in ML
Krishna Murthy Jatavallabhula, Bhairav Mehta, Tegan Maharaj, Amy Tabb, Khimya Khetarpal, Aditya Kusupati, Anna Rogers, Sara Hooker, Breandan Considine, Devi Parikh, Derek Nowrouzezahrai, Yoshua Bengio
Workshop
Fri 5:20 Spotlight 4: Théo Ladune et al., Conditional Coding for Flexible Learned Video Compression
Workshop
Fri 5:50 Energy-Based Models: Current Perspectives, Challenges, and Opportunities
Marc Dymetman, Adji Bousso Dieng, Hady Elsahar, Igor Mordatch, Marc'Aurelio Ranzato
Workshop
Fri 5:55 Hugo Larochelle
Workshop
Fri 6:00 A Roadmap to Never-Ending RL
Feryal Behbahani, Khimya Khetarpal, Louis Kirsch, Rose Wang, Annie Xie, Adam White, Doina Precup
Workshop
Fri 6:00 Workshop on Neural Architecture Search
Arber Zela, Aaron Klein, Frank Hutter, Liam Li, Jan Hendrik Metzen, Jovita Lukasik
Workshop
Fri 6:10 Voice2Series: Reprogramming Acoustic Models for Time Series Classification
Huck Yang
Workshop
Fri 6:30 Data-Efficient Training of Autoencoders for Mildly Non-Linear Problems
Muhammad Al-Digeil
Workshop
Fri 6:30 How Can Findings About The Brain Improve AI Systems?
Shinji Nishimoto, Leila Wehbe, Alexander Huth, Javier Turek, Nicole Beckage, Vy Vo, Mariya Toneva, Hsiang-Yun Chien, Shailee Jain, Richard Antonello
Workshop
Fri 6:45 Investigating Ground-level Ozone Formation: A Case Study in Taiwan
Yu-Wen Chen, Sourav Medya, Yi-Chun Chen
Workshop
Fri 7:00 Hugo Larochelle
Hugo Larochelle
Workshop
Fri 7:00 Synthetic Data Generation: Quality, Privacy, Bias
Sergul Aydore, Krishnaram Kenthapadi, Haipeng Chen, Edward Choi, Jamie Hayes, Mario Fritz, Rachel Cummings, Krishnaram Kenthapadi
Workshop
Fri 7:00 Workshop on Weakly Supervised Learning
Benjamin Roth, Barbara Plank, Alex Ratner, Katharina Kann, Dietrich Klakow, Michael Hedderich
Workshop
Fri 7:00 2nd Workshop on Practical ML for Developing Countries: Learning Under Limited/low Resource Scenarios
Esube Bekele, Waheeda Saib, Timnit Gebru, Meareg Hailemariam, Vukosi Marivate, Judy Gichoya
Workshop
Fri 7:05 Model Discovery in the Sparse Sampling Regime
Gert-Jan Both, Georges Tod, Remy Kusters
Workshop
Fri 7:10 Invited Speaker Dan Roth - Natural Language Understanding with Incidental Supervision
Dan Roth
Workshop
Fri 7:30 LambdaZero— Exascale Search of Molecules
Maksym Korablyov
Workshop
Fri 7:45 Workshop on Enormous Language Models: Perspectives and Benchmarks
Colin Raffel, Adam Roberts, Amanda Askell, Daphne Ippolito, Ethan Dyer, Guy Gur-Ari, Jared Kaplan, Jascha Sohl-Dickstein, Katherine Lee, Melanie Subbiah, Sam McCandlish, Tom Brown, William Fedus, Vedant Misra, Ambrose Slone, Daniel Freeman
Workshop
Fri 7:55 ICLR 2021 Workshop on Embodied Multimodal Learning (EML)
Ruohan Gao, Andrew Owens, Dinesh Jayaraman, Yuke Zhu, Jiajun Wu, Kristen Grauman
Workshop
Fri 8:00 Robust and reliable machine learning in the real world
Di Jin, Eric Wong, Yonatan Belinkov, Kai-Wei Chang, Zhijing Jin, Yanjun Qi, Aditi Raghunathan, Tristan Naumann, Mohit Bansal
Workshop
Fri 8:25 Invited Speaker Marine Carpuat - Weak Supervision for Cross-Lingual Semantic Analysis
Marine Carpuat
Workshop
Fri 8:30 Workshop on Distributed and Private Machine Learning
Fatemeh Mireshghallah, Praneeth Vepakomma, Ayush Chopra, Vivek Sharma, Abhishek Singh, Adam Smith, Ramesh Raskar, Gautam Kamath, Reza Shokri
Workshop
Fri 8:45 Feature Importance in a Deep Learning Climate Emulator
Wei Xu, Ray Ren, Ji Hwan Park, Shinjae Yoo, Balasubramanya T. Nadiga
Workshop
Fri 8:45 Deep Learning for Simulation
Zhitao Ying, Tailin Wu, Peter Battaglia, Rose Yu, Ryan P Adams, Jure Leskovec
Workshop
Fri 9:11 Bambara Language Dataset for Sentiment Analysis
chayma fourati
Workshop
Fri 9:40 Inference Risks for Machine Learning
David Evans
Workshop
Fri 10:30 Federated Learning with Taskonomy
Hadi Jamali-Rad, Mohammad Abdizadeh, Attila Szabó
Workshop
Fri 11:20 Invited Speaker Heng Ji - InfoSurgeon: Cross-media Weak Supervision for Knowledge-Element Level Fake News Detection
Heng Ji
Workshop
Fri 11:40 Deep Kernels with Probabilistic Embeddings for Small-Data Learning
Ankur Mallick
Workshop
Fri 11:48 Towards Robustness to Label Noise in Text Classification via Noise Modeling
Siddhant Garg
Workshop
Fri 12:00 Poster Spotlight "Recovering Quantitative Models of Human Information Processing with Differentiable Architecture Search"
Sebastian Musslick
Workshop
Fri 13:47 Round Table Panel Discussion
Workshop
Direct Federated Neural Architecture Search
Anubhav Garg, Amit Saha, Debojyoti Dutta
Workshop
On Privacy and Confidentiality of Communications in Organizational Graphs
Masoumeh Shafieinejad, Huseyin Inan, Marcello Hasegawa, Robert Sim
Workshop
Talk Less, Smile More: Reducing Communication with Distributed Auto-Differentiation
Bradley Baker, Vince Calhoun, Barak Pearlmutter, Sergey Plis
Workshop
CAUSALLY CONSTRAINED DATA SYNTHESIS FOR PRIVATE DATA RELEASE
Varun Chandrasekaran, Darren Edge, Somesh Jha, Amit Sharma, Cheng Zhang, Shruti Tople
Workshop
What is Going on Inside Recurrent Meta Reinforcement Learning Agents?
Safa Alver, Doina Precup
Workshop
CoMPS: Continual Meta Policy Search
Glen Berseth, Zhiwei Zhang, Chelsea Finn, Sergey Levine
Workshop
A Graphical Model Perspective on Federated Learning
Christos Louizos, Matthias Reisser, Joseph Soriaga, Max Welling