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 ]

342 Results

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 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 Overfitting for Fun and Profit: Instance-Adaptive Data Compression
Ties van Rozendaal, Iris Huijben, Taco Cohen
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 Exploring Balanced Feature Spaces for Representation Learning
Bingyi Kang, Yu Li, Sain Xie, Zehuan Yuan, Jiashi Feng
Poster
Mon 1:00 On InstaHide, Phase Retrieval, and Sparse Matrix Factorization
Sitan Chen, Xiaoxiao Li, Zhao Song, Danyang Zhuo
Poster
Mon 1:00 MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space
Tsz Him Cheung, Dit-Yan Yeung
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 ResNet After All: Neural ODEs and Their Numerical Solution
Katharina Ott, Prateek Katiyar, Philipp Hennig, Michael Tiemann
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 SALD: Sign Agnostic Learning with Derivatives
Matan Atzmon, Yaron Lipman
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 Set Prediction without Imposing Structure as Conditional Density Estimation
David W Zhang, Gertjan J Burghouts, Cees G Snoek
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 FairFil: Contrastive Neural Debiasing Method for Pretrained Text Encoders
Pengyu Cheng, Weituo Hao, Siyang Yuan, Shijing Si, Lawrence Carin
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 Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets
Hayeon Lee, Eunyoung Hyung, Sung Ju Hwang
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 Stabilized Medical Image Attacks
Gege Qi, Lijun GONG, Yibing Song, Kai Ma, Yefeng Zheng
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
Oral
Mon 4:00 Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding
David Klindt, Lukas Schott, Yash Sharma, Ivan Ustyuzhaninov, Wieland Brendel, Matthias Bethge, Dylan Paiton
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
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 from others' mistakes: Avoiding dataset biases without modeling them
Victor Sanh, Thomas Wolf, Yonatan Belinkov, Alexander M Rush
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 Scaling Symbolic Methods using Gradients for Neural Model Explanation
Subham Sahoo, Subhashini Venugopalan, Li Li, Rishabh Singh, Patrick Riley
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 Predicting Classification Accuracy When Adding New Unobserved Classes
Yuli Slavutsky, Yuval Benjamini
Poster
Mon 9:00 Open Question Answering over Tables and Text
wenhu chen, Ming-Wei Chang, Eva Schlinger, William Yang Wang, William Cohen
Poster
Mon 9:00 Understanding the failure modes of out-of-distribution generalization
Vaishnavh Nagarajan, Anders J Andreassen, Behnam Neyshabur
Poster
Mon 9:00 Multi-Time Attention Networks for Irregularly Sampled Time Series
Satya Narayan Shukla, Benjamin M Marlin
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 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 Gradient Projection Memory for Continual Learning
Gobinda Saha, Isha Garg, Kaushik Roy
Poster
Mon 9:00 Selectivity considered harmful: evaluating the causal impact of class selectivity in DNNs
Matthew Leavitt, Ari Morcos
Poster
Mon 9:00 Uncertainty Sets for Image Classifiers using Conformal Prediction
Anastasios Angelopoulos, Stephen Bates, Michael Jordan, Jitendra Malik
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 Zero-Cost Proxies for Lightweight NAS
Mohamed Abdelfattah, Abhinav Mehrotra, Łukasz Dudziak, Nic Lane
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 Using latent space regression to analyze and leverage compositionality in GANs
Lucy Chai, Jonas Wulff, Phillip Isola
Poster
Mon 9:00 A statistical theory of cold posteriors in deep neural networks
Laurence Aitchison
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 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 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 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 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 Shapley Explanation Networks
Rui Wang, Xiaoqian Wang, David Inouye
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 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 The Traveling Observer Model: Multi-task Learning Through Spatial Variable Embeddings
Elliot Meyerson, Risto Miikkulainen
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 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 Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding
David Klindt, Lukas Schott, Yash Sharma, Ivan Ustyuzhaninov, Wieland Brendel, Matthias Bethge, Dylan Paiton
Oral
Mon 11:15 Gradient Projection Memory for Continual Learning
Gobinda Saha, Isha Garg, Kaushik Roy
Spotlight
Mon 12:25 Sharpness-aware Minimization for Efficiently Improving Generalization
Pierre Foret, Ariel Kleiner, Hossein Mobahi, Behnam Neyshabur
Spotlight
Mon 12:35 Systematic generalisation with group invariant predictions
Faruk Ahmed, Yoshua Bengio, Harm van Seijen, Aaron Courville
Spotlight
Mon 12:45 On Statistical Bias In Active Learning: How and When to Fix It
Sebastian Farquhar, Yarin Gal, Tom Rainforth
Spotlight
Mon 13:20 Uncertainty Sets for Image Classifiers using Conformal Prediction
Anastasios Angelopoulos, Stephen Bates, Michael Jordan, Jitendra Malik
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 MoPro: Webly Supervised Learning with Momentum Prototypes
Junnan Li, Caiming Xiong, Steven Hoi
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 Improved Estimation of Concentration Under $\ell_p$-Norm Distance Metrics Using Half Spaces
Jack Prescott, XIAO ZHANG, David Evans
Poster
Mon 17:00 Spatio-Temporal Graph Scattering Transform
Chao Pan, Siheng Chen, Antonio Ortega
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 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 SOLAR: Sparse Orthogonal Learned and Random Embeddings
Tharun Medini Medini, Beidi Chen, Anshumali Shrivastava
Poster
Mon 17:00 SAFENet: A Secure, Accurate and Fast Neural Network Inference
Qian Lou, Yilin Shen, Hongxia Jin, Lei Jiang
Poster
Mon 17:00 Bypassing the Ambient Dimension: Private SGD with Gradient Subspace Identification
Yingxue Zhou, Steven Wu, Arindam Banerjee
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 Semi-supervised Keypoint Localization
Olga Moskvyak, Frederic Maire, Feras Dayoub, Mahsa Baktashmotlagh
Mon 17:00 ML in Korea
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 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 Parrot: Data-Driven Behavioral Priors for Reinforcement Learning
Avi Singh, Huihan Liu, Gaoyue Zhou, Albert Yu, Nicholas Rhinehart, Sergey Levine
Poster
Mon 17:00 Explaining the Efficacy of Counterfactually Augmented Data
Divyansh Kaushik, Amrith Setlur, Eduard H Hovy, Zachary Lipton
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 Decentralized Attribution of Generative Models
Changhoon Kim, Yi Ren, 'YZ' Yezhou Yang
Poster
Mon 17:00 Self-training For Few-shot Transfer Across Extreme Task Differences
Cheng Phoo, Bharath Hariharan
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 Selective Classification Can Magnify Disparities Across Groups
Erik Jones, Shiori Sagawa, Pang Wei Koh, Ananya Kumar, Percy Liang
Poster
Mon 17:00 Random Feature Attention
Hao Peng, Nikolaos Pappas, Dani Yogatama, Roy Schwartz, Noah Smith, Lingpeng Kong
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 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
Poster
Tue 1:00 Class Normalization for (Continual)? Generalized Zero-Shot Learning
Ivan Skorokhodov, Mohamed Elhoseiny
Poster
Tue 1:00 Refining Deep Generative Models via Discriminator Gradient Flow
Abdul Fatir Ansari, Ming Liang Ang, Harold Soh
Poster
Tue 1:00 On Self-Supervised Image Representations for GAN Evaluation
Stanislav Morozov, Andrey Voynov, Artem Babenko
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 FedMix: Approximation of Mixup under Mean Augmented Federated Learning
Tehrim Yoon, Sumin Shin, Sung Ju Hwang, Eunho Yang
Poster
Tue 1:00 Image GANs meet Differentiable Rendering for Inverse Graphics and Interpretable 3D Neural Rendering
Yuxuan Zhang, Wenzheng Chen, Huan Ling, Jun Gao, Yinan Zhang, Antonio Torralba, Sanja Fidler
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 Effective Abstract Reasoning with Dual-Contrast Network
Tao Zhuo, Mohan Kankanhalli
Poster
Tue 1:00 PDE-Driven Spatiotemporal Disentanglement
Jérémie DONA, Jean-Yves Franceschi, sylvain lamprier, patrick gallinari
Poster
Tue 1:00 Contemplating Real-World Object Classification
Ali Borji
Poster
Tue 1:00 Disambiguating Symbolic Expressions in Informal Documents
Dennis Müller, Cezary Kaliszyk
Poster
Tue 1:00 Complex Query Answering with Neural Link Predictors
Erik Arakelyan, Daniel Daza, Pasquale Minervini, Michael Cochez
Poster
Tue 1:00 MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering
Tsung Wei Tsai, Chongxuan Li, Jun Zhu
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 SkipW: Resource Adaptable RNN with Strict Upper Computational Limit
Tsiry MAYET, Anne Lambert, Pascal Le Guyadec, Francoise Le Bolzer, François Schnitzler
Spotlight
Tue 3:15 Autoregressive Entity Retrieval
Nicola De Cao, Gautier Izacard, Sebastian Riedel, Fabio Petroni
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
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 Supervised Contrastive Learning for Pre-trained Language Model Fine-tuning
Beliz Gunel, Jingfei Du, Alexis Conneau, Veselin Stoyanov
Poster
Tue 9:00 Teaching with Commentaries
Aniruddh Raghu, Maithra Raghu, Simon Kornblith, David Duvenaud, Geoffrey Hinton
Poster
Tue 9:00 Uncertainty Estimation in Autoregressive Structured Prediction
Andrey Malinin, Mark Gales
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 Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding
Sana Tonekaboni, Danny Eytan, Anna Goldenberg
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 Learning Parametrised Graph Shift Operators
George Dasoulas, Johannes Lutzeyer, Michalis Vazirgiannis
Poster
Tue 9:00 How Benign is Benign Overfitting ?
Amartya Sanyal, Puneet Dokania, Varun Kanade, Philip Torr
Poster
Tue 9:00 On the mapping between Hopfield networks and Restricted Boltzmann Machines
Matthew Smart, Anton Zilman
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 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 VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models
Zhisheng Xiao, Karsten Kreis, Jan Kautz, Arash Vahdat
Poster
Tue 9:00 Systematic generalisation with group invariant predictions
Faruk Ahmed, Yoshua Bengio, Harm van Seijen, Aaron Courville
Poster
Tue 9:00 SSD: A Unified Framework for Self-Supervised Outlier Detection
Vikash Sehwag, Mung Chiang, Prateek Mittal
Poster
Tue 9:00 The geometry of integration in text classification RNNs
Kyle Aitken, Vinay Ramasesh, Ankush Garg, Yuan Cao, David Sussillo, Niru Maheswaranathan
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
Oral
Tue 12:15 Image GANs meet Differentiable Rendering for Inverse Graphics and Interpretable 3D Neural Rendering
Yuxuan Zhang, Wenzheng Chen, Huan Ling, Jun Gao, Yinan Zhang, Antonio Torralba, Sanja Fidler
Oral
Tue 13:13 On the mapping between Hopfield networks and Restricted Boltzmann Machines
Matthew Smart, Anton Zilman
Spotlight
Tue 13:38 Long-tail learning via logit adjustment
Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Himanshu Jain, Andreas Veit, Sanjiv Kumar
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 The Importance of Pessimism in Fixed-Dataset Policy Optimization
Jacob Buckman, Carles Gelada, Marc G Bellemare
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 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 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 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 Topology-Aware Segmentation Using Discrete Morse Theory
Xiaoling Hu, Yusu Wang, Li Fuxin, Dimitris Samaras, Chao Chen
Poster
Tue 17:00 CcGAN: Continuous Conditional Generative Adversarial Networks for Image Generation
Xin Ding, Yongwei Wang, Zuheng Xu, William J Welch, Z. J Wang
Poster
Tue 17:00 DrNAS: Dirichlet Neural Architecture Search
Xiangning Chen, Ruochen Wang, Minhao Cheng, Xiaocheng Tang, Cho-Jui Hsieh
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 Concept Learners for Few-Shot Learning
Kaidi Cao, Maria Brbic, Jure Leskovec
Poster
Tue 17:00 Contextual Dropout: An Efficient Sample-Dependent Dropout Module
XINJIE FAN, Shujian Zhang, Korawat Tanwisuth, Xiaoning Qian, Mingyuan Zhou
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 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 Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning
Tsung-Wei Ke, Jyh-Jing Hwang, Stella Yu
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 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 Dataset Inference: Ownership Resolution in Machine Learning
Pratyush Maini, Mohammad Yaghini, Nicolas Papernot
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 19:35 Model-Based Visual Planning with Self-Supervised Functional Distances
Stephen Tian, Suraj Nair, Frederik Ebert, Sudeep Dasari, Ben Eysenbach, Chelsea Finn, Sergey Levine
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
Spotlight
Tue 21:33 Locally Free Weight Sharing for Network Width Search
Xiu Su, Shan You, Tao Huang, Fei Wang, Chen Qian, Changshui Zhang, Chang Xu
Poster
Wed 1:00 Bidirectional Variational Inference for Non-Autoregressive Text-to-Speech
Yoonhyung Lee, Joongbo Shin, Kyomin Jung
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 Knowledge distillation via softmax regression representation learning
Jing Yang, Brais Martinez, Adrian Bulat, Georgios Tzimiropoulos
Poster
Wed 1:00 Negative Data Augmentation
Abhishek Sinha, Kumar Ayush, Jiaming Song, Burak Uzkent, Hongxia Jin, Stefano Ermon
Poster
Wed 1:00 Locally Free Weight Sharing for Network Width Search
Xiu Su, Shan You, Tao Huang, Fei Wang, Chen Qian, Changshui Zhang, Chang Xu
Poster
Wed 1:00 Deep Neural Network Fingerprinting by Conferrable Adversarial Examples
Nils Lukas, Yuxuan Zhang, Florian Kerschbaum
Poster
Wed 1:00 Degree-Quant: Quantization-Aware Training for Graph Neural Networks
Shyam Tailor, Javier Fernandez-Marques, Nic Lane
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 No Cost Likelihood Manipulation at Test Time for Making Better Mistakes in Deep Networks
Shyamgopal Karthik, Ameya Prabhu, Puneet Dokania, Vineet Gandhi
Poster
Wed 1:00 Neural Delay Differential Equations
Qunxi Zhu, Yao Guo, Wei Lin
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 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 Disentangled Recurrent Wasserstein Autoencoder
Jun Han, Martin Min, Ligong Han, Li Erran Li, Xuan Zhang
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
Spotlight
Wed 4:20 Influence Estimation for Generative Adversarial Networks
Naoyuki Terashita, Hiroki Ohashi, Yuichi Nonaka, Takashi Kanemaru
Spotlight
Wed 4:30 Stabilized Medical Image Attacks
Gege Qi, Lijun GONG, Yibing Song, Kai Ma, Yefeng Zheng
Spotlight
Wed 4:40 Deep Neural Network Fingerprinting by Conferrable Adversarial Examples
Nils Lukas, Yuxuan Zhang, Florian Kerschbaum
Invited Talk
Wed 8:00 Is My Dataset Biased?
Kate Saenko
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 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 Faster Binary Embeddings for Preserving Euclidean Distances
Jinjie Zhang, Rayan Saab
Poster
Wed 9:00 Provably robust classification of adversarial examples with detection
Fatemeh Sheikholeslami, Ali Lotfi, Zico Kolter
Poster
Wed 9:00 IsarStep: a Benchmark for High-level Mathematical Reasoning
Wenda Li, Lei Yu, Yuhuai Wu, Lawrence Paulson
Poster
Wed 9:00 Probabilistic Numeric Convolutional Neural Networks
Marc Finzi, Roberto Bondesan, Max Welling
Poster
Wed 9:00 DARTS-: Robustly Stepping out of Performance Collapse Without Indicators
Xiangxiang Chu, Victor Wang, Bo Zhang, Shun Lu, Xiaolin Wei, Junchi Yan
Poster
Wed 9:00 Learning advanced mathematical computations from examples
François Charton, Amaury Hayat, Guillaume Lample
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 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 Iterated learning for emergent systematicity in VQA
Ankit Vani, Max Schwarzer, Yuchen Lu, Eeshan Dhekane, Aaron Courville
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 Sharpness-aware Minimization for Efficiently Improving Generalization
Pierre Foret, Ariel Kleiner, Hossein Mobahi, Behnam Neyshabur
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 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 Creative Sketch Generation
Songwei Ge, Vedanuj Goswami, Larry Zitnick, Devi Parikh
Poster
Wed 9:00 For self-supervised learning, Rationality implies generalization, provably
Yamini Bansal, Gal Kaplun, Boaz Barak
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 PC2WF: 3D Wireframe Reconstruction from Raw Point Clouds
Yujia Liu, Stefano D'Aronco, Konrad Schindler, Jan D Wegner
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 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 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 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 DeepAveragers: Offline Reinforcement Learning By Solving Derived Non-Parametric MDPs
aayam shrestha, Stefan Lee, Prasad Tadepalli, Alan Fern
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 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 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
Spotlight
Wed 13:28 VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models
Zhisheng Xiao, Karsten Kreis, Jan Kautz, Arash Vahdat
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 16:15 EigenGame: PCA as a Nash Equilibrium
Ian Gemp, Brian McWilliams, Claire Vernade, Thore Graepel
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 AdaSpeech: Adaptive Text to Speech for Custom Voice
Mingjian Chen, Xu Tan, Bohan Li, Eric Liu, Tao Qin, sheng zhao, Tie-Yan Liu
Poster
Wed 17:00 Graph-Based Continual Learning
Binh Tang, David S Matteson
Poster
Wed 17:00 Meta Back-Translation
Hieu Pham, Xinyi Wang, Yiming Yang, Graham Neubig
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 Empirical Analysis of Unlabeled Entity Problem in Named Entity Recognition
Yangming Li, lemao liu, Shuming Shi
Poster
Wed 17:00 In Search of Lost Domain Generalization
Ishaan Gulrajani, David Lopez-Paz
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 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 Adaptive Universal Generalized PageRank Graph Neural Network
Eli Chien, Jianhao Peng, Pan Li, Olgica Milenkovic
Poster
Wed 17:00 CoCo: Controllable Counterfactuals for Evaluating Dialogue State Trackers
Shiyang Li, Semih Yavuz, Kazuma Hashimoto, Jia Li, Tong Niu, Nazneen Rajani, Xifeng Yan, Yingbo Zhou, Caiming Xiong
Poster
Wed 17:00 Influence Functions in Deep Learning Are Fragile
Samyadeep Basu, Phil Pope, Soheil Feizi
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 A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks
Renjie Liao, Raquel Urtasun, Richard Zemel
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 Improved Autoregressive Modeling with Distribution Smoothing
Chenlin Meng, Jiaming Song, Yang Song, Shengjia Zhao, Stefano Ermon
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 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 Estimating informativeness of samples with Smooth Unique Information
Hrayr Harutyunyan, Alessandro Achille, Giovanni Paolini, Orchid Majumder, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
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 Robust Overfitting may be mitigated by properly learned smoothening
Tianlong Chen, Zhenyu Zhang, Sijia Liu, Shiyu Chang, Zhangyang Wang
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 CPR: Classifier-Projection Regularization for Continual Learning
Sungmin Cha, Hsiang Hsu, Taebaek Hwang, Flavio Calmon, Taesup Moon
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 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 Model-Based Visual Planning with Self-Supervised Functional Distances
Stephen Tian, Suraj Nair, Frederik Ebert, Sudeep Dasari, Ben Eysenbach, Chelsea Finn, Sergey Levine
Oral
Wed 19:00 Improved Autoregressive Modeling with Distribution Smoothing
Chenlin Meng, Jiaming Song, Yang Song, Shengjia Zhao, Stefano Ermon
Spotlight
Wed 20:10 Graph-Based Continual Learning
Binh Tang, David S Matteson
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
Oral
Thu 0:15 Complex Query Answering with Neural Link Predictors
Erik Arakelyan, Daniel Daza, Pasquale Minervini, Michael Cochez
Poster
Thu 1:00 Influence Estimation for Generative Adversarial Networks
Naoyuki Terashita, Hiroki Ohashi, Yuichi Nonaka, Takashi Kanemaru
Poster
Thu 1:00 Autoregressive Entity Retrieval
Nicola De Cao, Gautier Izacard, Sebastian Riedel, Fabio Petroni
Poster
Thu 1:00 Retrieval-Augmented Generation for Code Summarization via Hybrid GNN
Shangqing Liu, Yu Chen, Xiaofei Xie, Siow Jing Kai, Yang Liu
Poster
Thu 1:00 Certify or Predict: Boosting Certified Robustness with Compositional Architectures
Mark Niklas Mueller, Mislav Balunovic, Martin Vechev
Poster
Thu 1:00 Adaptive and Generative Zero-Shot Learning
Yu-Ying Chou, Hsuan-Tien (Tien) Lin, Tyng-Luh Liu
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 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 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 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 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 The inductive bias of ReLU networks on orthogonally separable data
Mary Phuong, Christoph H Lampert
Poster
Thu 1:00 Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks
Jan Schuchardt, Aleksandar Bojchevski, Johannes Klicpera, Stephan Günnemann
Poster
Thu 1:00 ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations
Rishabh Tiwari, Udbhav Bamba, Arnav Chavan, Deepak Gupta
Poster
Thu 1:00 Free Lunch for Few-shot Learning: Distribution Calibration
Shuo Yang, Lu Liu, Min Xu
Spotlight
Thu 4:55 On Self-Supervised Image Representations for GAN Evaluation
Stanislav Morozov, Andrey Voynov, Artem Babenko
Spotlight
Thu 5:05 Retrieval-Augmented Generation for Code Summarization via Hybrid GNN
Shangqing Liu, Yu Chen, Xiaofei Xie, Siow Jing Kai, Yang Liu
Poster
Thu 9:00 Directed Acyclic Graph Neural Networks
Veronika Thost, Jie Chen
Poster
Thu 9:00 Improving Zero-Shot Voice Style Transfer via Disentangled Representation Learning
Siyang Yuan, Pengyu Cheng, Ruiyi Zhang, Weituo Hao, Zhe Gan, Lawrence Carin
Poster
Thu 9:00 EEC: Learning to Encode and Regenerate Images for Continual Learning
Ali Ayub, Alan Wagner
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 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 Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning
Kanil Patel, William H Beluch, Bin Yang, Michael Pfeiffer, Dan Zhang
Poster
Thu 9:00 Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma Augmented Gaussian Processes
Jake Snell, Richard Zemel
Poster
Thu 9:00 Improving VAEs' Robustness to Adversarial Attack
Matthew Willetts, Alexander Camuto, Tom Rainforth, S Roberts, Christopher Holmes
Poster
Thu 9:00 Understanding and Improving Lexical Choice in Non-Autoregressive Translation
Liam Ding, Longyue Wang, Xuebo Liu, Derek Wong, Dacheng Tao, Zhaopeng Tu
Poster
Thu 9:00 Learning to Recombine and Resample Data For Compositional Generalization
Ekin Akyürek, Afra Feyza Akyürek, Jacob Andreas
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 Uncertainty in Gradient Boosting via Ensembles
Andrey Malinin, Liudmila Prokhorenkova, Aleksei Ustimenko
Poster
Thu 9:00 Private Post-GAN Boosting
Marcel Neunhoeffer, Steven Wu, Cynthia Dwork
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 Robust early-learning: Hindering the memorization of noisy labels
Xiaobo Xia, Tongliang Liu, Bo Han, Chen Gong, Nannan Wang, Zongyuan Ge, Yi Chang
Poster
Thu 9:00 Generative Language-Grounded Policy in Vision-and-Language Navigation with Bayes' Rule
Shuhei Kurita, Kyunghyun Cho
Poster
Thu 9:00 EigenGame: PCA as a Nash Equilibrium
Ian Gemp, Brian McWilliams, Claire Vernade, Thore Graepel
Poster
Thu 9:00 End-to-End Egospheric Spatial Memory
Daniel Lenton, Stephen James, Ronald Clark, Andrew Davison
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
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 Variational Information Bottleneck for Effective Low-Resource Fine-Tuning
Rabeeh Karimi Mahabadi, Yonatan Belinkov, James Henderson
Poster
Thu 9:00 Dataset Condensation with Gradient Matching
Bo ZHAO, Konda Reddy Mopuri, Hakan Bilen
Poster
Thu 9:00 Dataset Meta-Learning from Kernel Ridge-Regression
Timothy Nguyen, Zhourong Chen, Jaehoon Lee
Poster
Thu 9:00 Dual-mode ASR: Unify and Improve Streaming ASR with Full-context Modeling
Jiahui Yu, Wei Han, Anmol Gulati, Chung-Cheng Chiu, Bo Li, Tara Sainath, Yonghui Wu, Ruoming Pang
Poster
Thu 9:00 BREEDS: Benchmarks for Subpopulation Shift
Shibani Santurkar, Dimitris Tsipras, Aleksander Madry
Oral
Thu 11:30 When Do Curricula Work?
Xiaoxia (Shirley) Wu, Ethan Dyer, Behnam Neyshabur
Spotlight
Thu 12:30 DeepAveragers: Offline Reinforcement Learning By Solving Derived Non-Parametric MDPs
aayam shrestha, Stefan Lee, Prasad Tadepalli, Alan Fern
Oral
Thu 13:15 Self-training For Few-shot Transfer Across Extreme Task Differences
Cheng Phoo, Bharath Hariharan
Spotlight
Thu 13:40 BUSTLE: Bottom-Up Program Synthesis Through Learning-Guided Exploration
Augustus Odena, Kensen Shi, David Bieber, Rishabh Singh, Charles Sutton, Hanjun Dai
Spotlight
Thu 13:50 Disentangled Recurrent Wasserstein Autoencoder
Jun Han, Martin Min, Ligong Han, Li Erran Li, Xuan Zhang
Invited Talk
Thu 16:00 Self-Supervision for Learning from the Bottom Up
Alyosha Efros
Poster
Thu 17:00 Distributional Sliced-Wasserstein and Applications to Generative Modeling
Khai Nguyen, Nhat Ho, Tung Pham, Hung Bui
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 Group Equivariant Generative Adversarial Networks
Neel Dey, Antong Chen, Soheil Ghafurian
Poster
Thu 17:00 Cross-Attentional Audio-Visual Fusion for Weakly-Supervised Action Localization
Juntae Lee, Mihir Jain, Hyoungwoo Park, Sungrack Yun
Poster
Thu 17:00 HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients
Enmao Diao, Jie Ding, VAHID TAROKH
Poster
Thu 17:00 Auto Seg-Loss: Searching Metric Surrogates for Semantic Segmentation
Hao Li, Chenxin Tao, Xizhou Zhu, Xiaogang Wang, Gao Huang, Jifeng Dai
Poster
Thu 17:00 Calibration of Neural Networks using Splines
Kartik Gupta, Amir Rahimi, Thalaiyasingam Ajanthan, Thomas Mensink, Cristian Sminchisescu, Richard Hartley
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 $i$-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning
Kibok Lee, Yian Zhu, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin, Honglak Lee
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 Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval
Wenhan Xiong, Lorraine Li, Srini Iyer, Jingfei Du, Patrick Lewis, William Yang Wang, Yashar Mehdad, Scott Yih, Sebastian Riedel, Douwe Kiela, Barlas Oguz
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 When Do Curricula Work?
Xiaoxia (Shirley) Wu, Ethan Dyer, Behnam Neyshabur
Poster
Thu 17:00 Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization
Kaidi Cao, Yining Chen, Junwei Lu, Nikos Arechiga, Adrien Gaidon, Tengyu Ma
Poster
Thu 17:00 GAN2GAN: Generative Noise Learning for Blind Denoising with Single Noisy Images
Sungmin Cha, Taeeon Park, Byeongjoon Kim, Jongduk Baek, Taesup Moon
Poster
Thu 17:00 Generative Scene Graph Networks
Fei Deng, Zhuo Zhi, Donghun Lee, Sungjin Ahn
Poster
Thu 17:00 Fully Unsupervised Diversity Denoising with Convolutional Variational Autoencoders
Mangal Prakash, Alexander Krull, Florian Jug
Poster
Thu 17:00 Convex Regularization behind Neural Reconstruction
Arda Sahiner, Morteza Mardani, Batu Ozturkler, Mert Pilanci, John M Pauly
Poster
Thu 17:00 Estimating and Evaluating Regression Predictive Uncertainty in Deep Object Detectors
Ali Harakeh, Steven L Waslander
Poster
Thu 17:00 CPT: Efficient Deep Neural Network Training via Cyclic Precision
Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan Lin
Poster
Thu 17:00 Neural Pruning via Growing Regularization
Huan Wang, Can Qin, Yulun Zhang, Yun Fu
Poster
Thu 17:00 Prototypical Representation Learning for Relation Extraction
Ning Ding, Xiaobin Wang, Yao Fu, Guangwei Xu, Rui Wang, Pengjun Xie, Ying Shen, Fei Huang, Hai-Tao Zheng, Rui Zhang
Spotlight
Thu 20:05 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
Spotlight
Thu 20:15 Random Feature Attention
Hao Peng, Nikolaos Pappas, Dani Yogatama, Roy Schwartz, Noah Smith, Lingpeng Kong
Spotlight
Thu 20:25 Learning with Feature-Dependent Label Noise: A Progressive Approach
Yikai Zhang, Songzhu Zheng, Pengxiang Wu, Mayank Goswami, Chao Chen
Spotlight
Thu 21:08 Topology-Aware Segmentation Using Discrete Morse Theory
Xiaoling Hu, Yusu Wang, Li Fuxin, Dimitris Samaras, Chao Chen
Spotlight
Thu 21:28 Distributional Sliced-Wasserstein and Applications to Generative Modeling
Khai Nguyen, Nhat Ho, Tung Pham, Hung Bui
Workshop
Fri 3:05 Model Selection's Disparate Impact in Real-World Deep Learning Applications
Jessica Forde, A. Feder Cooper
Workshop
Fri 3:25 Do Input Gradients Highlight Discriminative Features?
Harshay Shah
Workshop
Fri 4:45 Oral 1: Yann Dubois et al., Lossy Compression for Lossless Prediction
Taco Cohen
Workshop
Fri 6:18 Adversarial Data Augmentation Improves Unsupervised Machine Learning
Chia-Yi Hsu
Workshop
Fri 6:22 On Adversarial Robustness: A Neural Architecture Search perspective
Chaitanya Devaguptapu
Workshop
Fri 6:26 Submodular Mutual Information for Targeted Data Subset Selection
Suraj Kothawade
Workshop
Fri 6:30 Data-Efficient Training of Autoencoders for Mildly Non-Linear Problems
Muhammad Al-Digeil
Workshop
Fri 6:34 Min-Entropy Sampling Might Lead to Better Generalization in Deep Text Classification, Nimrah Shakeel
Nimrah Shakeel
Workshop
Fri 7:00 Interpretable Recommender System With Heterogeneous Information: A Geometric Deep Learning Perspective
Yan Leng
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 7:00 Synthetic Data Generation: Quality, Privacy, Bias
Sergul Aydore, Krishnaram Kenthapadi, Haipeng Chen, Edward Choi, Jamie Hayes, Mario Fritz, Rachel Cummings, Krishnaram Kenthapadi
Workshop
Fri 7:25 Physically-Consistent Generative Adversarial Networks for Coastal Flood Visualization.
Björn Lütjens, brandon leshchinskiy, Christian Requena-Mesa, Natalia Diaz Rodriguez, Aruna Sankaranarayanan, Aaron Piña, Yarin Gal, Chedy Raissi, Alexander Lavin, Dava Newman
Workshop
Fri 8:15 Boosting Classification Accuracy of Fertile Sperm Cell Images leveraging cDCGAN
Dipam Paul
Workshop
Fri 8:36 Fairly Estimating Socioeconomic Status Under Costly Feature Acquisition
Kush R Varshney
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 11:18 Leveraging Public Data for Practical Private Query Release
Terrance Liu, Giuseppe Vietri, Thomas Steinke, Jonathan Ullman, Steven Wu
Workshop
Fri 11:40 Deep Kernels with Probabilistic Embeddings for Small-Data Learning
Ankur Mallick
Workshop
Fri 11:44 Boosting Classification Accuracy of Fertile Sperm Cell Images leveraging cDCGAN
Dipam Paul
Workshop
Fri 11:48 Towards Robustness to Label Noise in Text Classification via Noise Modeling
Siddhant Garg
Workshop
Fri 12:51 "Ethical Considerations of Generative AI" by Emily Denton, Google’s Ethical AI team
Emily Denton
Workshop
Fri 14:25 Invited Speaker Lu Jiang - Robust Deep Learning and Applications
Lu Jiang
Workshop
Fri 15:25 Invited Speaker Paroma Varma - Snorkel: Programmatically Labeling Training Data
Paroma Varma
Workshop
FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks
Chaoyang He, Keshav Balasubramanian, Emir Ceyani, Yu Rong, Junzhou Huang, Murali Annavaram, Salman Avestimehr
Workshop
OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation
Jongmin Lee, Wonseok Jeon, Byung-Jun Lee, Joelle Pineau, Kee-Eung Kim
Workshop
Prior-Free Auctions for the Demand Side of Federated Learning
Andreas Haupt, Vaikkunth Mugunthan
Workshop
Preventing Unauthorized Use of Proprietary Data: Poisoning for Secure Dataset Release
Liam H Fowl, Ping-yeh Chiang, Micah Goldblum, Jonas Geiping, Tom Goldstein
Workshop
PyVertical: A Vertical Federated Learning Framework for Multi-headed SplitNN
Daniele Romanini, Adam Hall, Pavlos Papadopoulos, Tom Titcombe, Abbas Ismail, Tudor Cebere, Robert Sandmann, Robin Roehm, Michael Hoeh
Workshop
Layer-wise Characterization of Latent Information Leakage in Federated Learning
Fan Mo, Anastasia Borovykh, Mohammad Malekzadeh, Hamed Haddadi, Soteris Demetriou