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 ]

524 Results

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 Tomographic Auto-Encoder: Unsupervised Bayesian Recovery of Corrupted Data
Francesco Tonolini, Pablo Garcia Moreno, Andreas Damianou, Roderick Murray-Smith
Poster
Mon 1:00 Mutual Information State Intrinsic Control
Rui Zhao, Yang Gao, Pieter Abbeel, Volker Tresp, Wei Xu
Poster
Mon 1:00 Semantic Re-tuning with Contrastive Tension
Fredrik Carlsson, Amaru C Gyllensten, Evangelia Gogoulou, Erik Y Hellqvist, Magnus Sahlgren
Poster
Mon 1:00 Solving Compositional Reinforcement Learning Problems via Task Reduction
Yunfei Li, Yilin Wu, Huazhe Xu, Xiaolong Wang, Yi Wu
Poster
Mon 1:00 Progressive Skeletonization: Trimming more fat from a network at initialization
Pau de Jorge Aranda, Amartya Sanyal, Harkirat Singh Behl, Philip Torr, Grégory Rogez, Puneet Dokania
Poster
Mon 1:00 Scalable Transfer Learning with Expert Models
Joan Puigcerver Puigcerver i Perez, Carlos Riquelme, Basil Mustafa, Cedric Renggli, André Susano Pinto, Sylvain Gelly, Daniel Keysers, Neil Houlsby
Poster
Mon 1:00 Batch Reinforcement Learning Through Continuation Method
Yijie Guo, Shengyu Feng, Nicolas Le Roux, Ed H. Chi, Honglak Lee, Minmin Chen
Poster
Mon 1:00 Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs
Cheng Wang, Carolin Lawrence, Mathias Niepert
Poster
Mon 1:00 Domain Generalization with MixStyle
Kaiyang Zhou, Yongxin Yang, Yu Qiao, Tao Xiang
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 SaliencyMix: A Saliency Guided Data Augmentation Strategy for Better Regularization
A F M Shahab Uddin, Mst. Sirazam Monira, Wheemyung Shin, TaeChoong Chung, Sung-Ho Bae
Poster
Mon 1:00 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 Temporally-Extended ε-Greedy Exploration
Will Dabney, Georg Ostrovski, Andre Barreto
Poster
Mon 1:00 Randomized Ensembled Double Q-Learning: Learning Fast Without a Model
Xinyue Chen, Che Wang, Zijian Zhou, Keith Ross
Poster
Mon 1:00 MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space
Tsz Him Cheung, Dit-Yan Yeung
Poster
Mon 1:00 Parameter-Based Value Functions
Francesco Faccio, Louis Kirsch, Jürgen Schmidhuber
Poster
Mon 1:00 Wasserstein Embedding for Graph Learning
Soheil Kolouri, Navid Naderializadeh, Gustavo K Rohde, Heiko Hoffmann
Poster
Mon 1:00 Predicting Infectiousness for Proactive Contact Tracing
Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif B Muller, Meng Qu, victor schmidt, Pierre-luc St-charles, hannah alsdurf, Olexa Bilaniuk, david buckeridge, Gaétan Marceau Caron, pierre carrier, Joumana Ghosn, satya gagne, Chris J Pal, Irina Rish, Bernhard Schoelkopf, abhinav sharma, Jian Tang, Andrew Williams
Poster
Mon 1:00 QPLEX: Duplex Dueling Multi-Agent Q-Learning
Jianhao Wang, Zhizhou Ren, Terry Liu, Yang Yu, Chongjie Zhang
Poster
Mon 1:00 Spatially Structured Recurrent Modules
Nasim Rahaman, Anirudh Goyal, Waleed Gondal, Manuel Wuthrich, Stefan Bauer, Yash Sharma, Yoshua Bengio, Bernhard Schoelkopf
Poster
Mon 1:00 ResNet After All: Neural ODEs and Their Numerical Solution
Katharina Ott, Prateek Katiyar, Philipp Hennig, Michael Tiemann
Poster
Mon 1:00 MELR: Meta-Learning via Modeling Episode-Level Relationships for Few-Shot Learning
Nanyi Fei, Zhiwu Lu, Tao Xiang, Songfang Huang
Poster
Mon 1:00 Towards Robust Neural Networks via Close-loop Control
Zhuotong Chen, Qianxiao Li, Zheng Zhang
Poster
Mon 1:00 Signatory: differentiable computations of the signature and logsignature transforms, on both CPU and GPU
Patrick Kidger, Terry Lyons
Poster
Mon 1:00 FairFil: Contrastive Neural Debiasing Method for Pretrained Text Encoders
Pengyu Cheng, Weituo Hao, Siyang Yuan, Shijing Si, Lawrence Carin
Spotlight
Mon 3:40 Generalization in data-driven models of primary visual cortex
Konstantin-Klemens Lurz, Mohammad Bashiri, Konstantin Willeke, Akshay Jagadish, Eric Wang, Edgar Walker, Santiago Cadena Cadena, Taliah Muhammad, Erick M Cobos, Andreas Tolias, Alexander S Ecker, Fabian Sinz
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
Oral
Mon 5:15 Do 2D GANs Know 3D Shape? Unsupervised 3D Shape Reconstruction from 2D Image GANs
Xingang Pan, Bo DAI, Ziwei Liu, Chen Change Loy, Ping Luo
Spotlight
Mon 5:45 Contrastive Divergence Learning is a Time Reversal Adversarial Game
Omer Yair, Tomer Michaeli
Invited Talk
Mon 8:00 Moving beyond the fairness rhetoric in machine learning
Timnit Gebru
Poster
Mon 9:00 Learning "What-if" Explanations for Sequential Decision-Making
Ioana Bica, Dan Jarrett, Alihan Hüyük, Mihaela van der Schaar
Poster
Mon 9:00 Symmetry-Aware Actor-Critic for 3D Molecular Design
Gregor Simm, Robert Pinsler, Gábor Csányi, José Miguel Hernández Lobato
Poster
Mon 9:00 Teaching Temporal Logics to Neural Networks
Christopher Hahn, Frederik Schmitt, Jens Kreber, Markus Rabe, Bernd Finkbeiner
Poster
Mon 9:00 Predicting Inductive Biases of Pre-Trained Models
Charles Lovering, Rohan Jha, Tal Linzen, Ellie Pavlick
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 Graph Convolution with Low-rank Learnable Local Filters
Xiuyuan Cheng, Zichen Miao, Qiang Qiu
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 On Statistical Bias In Active Learning: How and When to Fix It
Sebastian Farquhar, Yarin Gal, Tom Rainforth
Poster
Mon 9:00 Training GANs with Stronger Augmentations via Contrastive Discriminator
Jongheon Jeong, Jinwoo Shin
Poster
Mon 9:00 Adaptive Federated Optimization
Sashank Reddi, Zachary Charles, Manzil Zaheer, Zachary Garrett, Keith Rush, Jakub Konečný, Sanjiv Kumar, Brendan McMahan
Poster
Mon 9:00 Scaling Symbolic Methods using Gradients for Neural Model Explanation
Subham Sahoo, Subhashini Venugopalan, Li Li, Rishabh Singh, Patrick Riley
Poster
Mon 9:00 Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers
Ben Eysenbach, Shreyas Chaudhari, Swapnil Asawa, Sergey Levine, Ruslan Salakhutdinov
Poster
Mon 9:00 Multi-Time Attention Networks for Irregularly Sampled Time Series
Satya Narayan Shukla, Benjamin M Marlin
Poster
Mon 9:00 What Should Not Be Contrastive in Contrastive Learning
Tete Xiao, Xiaolong Wang, Alyosha Efros, trevor darrell
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 Share or Not? Learning to Schedule Language-Specific Capacity for Multilingual Translation
Biao Zhang, Ankur Bapna, Rico Sennrich, Orhan Firat
Poster
Mon 9:00 The Traveling Observer Model: Multi-task Learning Through Spatial Variable Embeddings
Elliot Meyerson, Risto Miikkulainen
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 Reset-Free Lifelong Learning with Skill-Space Planning
Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch
Mon 9:00 Philosophy and AGI (#1)
Poster
Mon 9:00 Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction
Wei Deng, Qi Feng, Georgios Karagiannis, Guang Lin, Faming Liang
Poster
Mon 9:00 Pruning Neural Networks at Initialization: Why Are We Missing the Mark?
Jonathan Frankle, Gintare Dziugaite, Anonymous A Author, Michael Carbin
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 Trajectory Prediction using Equivariant Continuous Convolution
Robin Walters, Jinxi Li, Rose Yu
Poster
Mon 9:00 Disentangling 3D Prototypical Networks for Few-Shot Concept Learning
Mihir Prabhudesai, Shamit Lal, Darshan Patil, Hsiao-Yu Tung, Adam Harley, Katerina Fragkiadaki
Poster
Mon 9:00 Selectivity considered harmful: evaluating the causal impact of class selectivity in DNNs
Matthew Leavitt, Ari Morcos
Poster
Mon 9:00 Fast convergence of stochastic subgradient method under interpolation
Huang Fang, Zhenan Fan, Michael Friedlander
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 On the Impossibility of Global Convergence in Multi-Loss Optimization
Alistair Letcher
Poster
Mon 9:00 Rapid Task-Solving in Novel Environments
Samuel Ritter, Ryan Faulkner, Laurent Sartran, Adam Santoro, Matthew Botvinick, David Raposo
Poster
Mon 9:00 Learning with AMIGo: Adversarially Motivated Intrinsic Goals
Andres Campero, Roberta Raileanu, Heinrich Kuttler, Joshua B Tenenbaum, Tim Rocktaeschel, Ed Grefenstette
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 Overparameterisation and worst-case generalisation: friend or foe?
Aditya Krishna Menon, Ankit Singh Rawat, Sanjiv Kumar
Poster
Mon 9:00 Planning from Pixels using Inverse Dynamics Models
Keiran Paster, Sheila McIlraith, Jimmy Ba
Poster
Mon 9:00 Plan-Based Relaxed Reward Shaping for Goal-Directed Tasks
Ingmar Schubert, Oz Oguz, Marc Toussaint
Poster
Mon 9:00 Self-Supervised Policy Adaptation during Deployment
Nicklas Hansen, Rishabh Jangir, Yu Sun, Guillem Alenyà, Pieter Abbeel, Alyosha Efros, Lerrel Pinto, Xiaolong Wang
Poster
Mon 9:00 On the role of planning in model-based deep reinforcement learning
Jessica Hamrick, Abram Friesen, Feryal Behbahani, Arthur Guez, Fabio Viola, Sims Witherspoon, Thomas Anthony, Lars Buesing, Petar Veličković, Theo Weber
Poster
Mon 9:00 The Risks of Invariant Risk Minimization
Elan Rosenfeld, Pradeep K Ravikumar, Andrej Risteski
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
Poster
Mon 9:00 Shapley Explanation Networks
Rui Wang, Xiaoqian Wang, David Inouye
Spotlight
Mon 11:45 Geometry-Aware Gradient Algorithms for Neural Architecture Search
Liam Li, Misha Khodak, Nina Balcan, Ameet Talwalkar
Mon 12:00 Operationalizing AI for Healthcare
Spotlight
Mon 12:05 Generalization bounds via distillation
Daniel Hsu, Ziwei Ji, Matus Telgarsky, Lan Wang
Spotlight
Mon 12:45 On Statistical Bias In Active Learning: How and When to Fix It
Sebastian Farquhar, Yarin Gal, Tom Rainforth
Spotlight
Mon 13:40 Gradient Vaccine: Investigating and Improving Multi-task Optimization in Massively Multilingual Models
Zirui Wang, Yulia Tsvetkov, Orhan Firat, Yuan Cao
Spotlight
Mon 13:50 Watch-And-Help: A Challenge for Social Perception and Human-AI Collaboration
Xavier Puig, Tianmin Shu, Shuang Li, Zilin Wang, Andrew Liao, Joshua B Tenenbaum, Sanja Fidler, Antonio Torralba
Spotlight
Mon 14:00 Predicting Infectiousness for Proactive Contact Tracing
Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif B Muller, Meng Qu, victor schmidt, Pierre-luc St-charles, hannah alsdurf, Olexa Bilaniuk, david buckeridge, Gaétan Marceau Caron, pierre carrier, Joumana Ghosn, satya gagne, Chris J Pal, Irina Rish, Bernhard Schoelkopf, abhinav sharma, Jian Tang, Andrew Williams
Poster
Mon 17:00 Remembering for the Right Reasons: Explanations Reduce Catastrophic Forgetting
Sayna Ebrahimi, Suzanne Petryk, Akash Gokul, William Gan, Joseph E Gonzalez, Marcus Rohrbach, trevor darrell
Poster
Mon 17:00 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 Rethinking Positional Encoding in Language Pre-training
Guolin Ke, Di He, Tie-Yan Liu
Poster
Mon 17:00 PlasticineLab: A Soft-Body Manipulation Benchmark with Differentiable Physics
Zhiao Huang, Yuanming Hu, Tao Du, Siyuan Zhou, Hao Su, Joshua B Tenenbaum, Chuang Gan
Poster
Mon 17:00 Why resampling outperforms reweighting for correcting sampling bias with stochastic gradients
Jing An, Lexing Ying, Yuhua Zhu
Poster
Mon 17:00 One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks
Atish Agarwala, Abhimanyu Das, Brendan Juba, Rina Panigrahy, Vatsal Sharan, Xin Wang, Qiuyi Zhang
Poster
Mon 17:00 Personalized Federated Learning with First Order Model Optimization
Michael Zhang, Karan Sapra, Sanja Fidler, Serena Yeung, Jose M. Alvarez
Poster
Mon 17:00 Sequential Density Ratio Estimation for Simultaneous Optimization of Speed and Accuracy
Akinori Ebihara, Taiki Miyagawa, Kazuyuki Sakurai, Hitoshi Imaoka
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 MoPro: Webly Supervised Learning with Momentum Prototypes
Junnan Li, Caiming Xiong, Steven Hoi
Poster
Mon 17:00 The Intrinsic Dimension of Images and Its Impact on Learning
Phil Pope, Chen Zhu, Ahmed Abdelkader, Micah Goldblum, Tom Goldstein
Mon 17:00 ML in Korea
Poster
Mon 17:00 The Deep Bootstrap Framework: Good Online Learners are Good Offline Generalizers
Preetum Nakkiran, Behnam Neyshabur, Hanie Sedghi
Poster
Mon 17:00 Random Feature Attention
Hao Peng, Nikolaos Pappas, Dani Yogatama, Roy Schwartz, Noah Smith, Lingpeng Kong
Poster
Mon 17:00 Robust Reinforcement Learning on State Observations with Learned Optimal Adversary
Huan Zhang, Hongge Chen, Duane S Boning, Cho-Jui Hsieh
Poster
Mon 17:00 Optimizing Memory Placement using Evolutionary Graph Reinforcement Learning
Shauharda Khadka, Estelle Aflalo, Mattias Marder, Avrech Ben-David, Santiago Miret, Shie Mannor, Tamir Hazan, Hanlin Tang, Somdeb Majumdar
Poster
Mon 17:00 Learning A Minimax Optimizer: A Pilot Study
Jiayi Shen, Xiaohan Chen, Howard Heaton, Tianlong Chen, Jialin Liu, Wotao Yin, Zhangyang Wang
Poster
Mon 17:00 Tilted Empirical Risk Minimization
Tian Li, Ahmad Beirami, Maziar Sanjabi, Virginia Smith
Poster
Mon 17:00 When Optimizing $f$-Divergence is Robust with Label Noise
Jiaheng Wei, Yang Liu
Poster
Mon 17:00 Incorporating Symmetry into Deep Dynamics Models for Improved Generalization
Rui Wang, Robin Walters, Rose Yu
Poster
Mon 17:00 Rethinking Architecture Selection in Differentiable NAS
Ruochen Wang, Minhao Cheng, Xiangning Chen, Xiaocheng Tang, Cho-Jui Hsieh
Poster
Mon 17:00 UPDeT: Universal Multi-agent RL via Policy Decoupling with Transformers
Siyi Hu, Fengda Zhu, Xiaojun Chang, Xiaodan Liang
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 Semi-supervised Keypoint Localization
Olga Moskvyak, Frederic Maire, Feras Dayoub, Mahsa Baktashmotlagh
Poster
Mon 17:00 Explaining the Efficacy of Counterfactually Augmented Data
Divyansh Kaushik, Amrith Setlur, Eduard H Hovy, Zachary Lipton
Poster
Mon 17:00 What are the Statistical Limits of Offline RL with Linear Function Approximation?
Ruosong Wang, Dean Foster, Sham M Kakade
Poster
Mon 17:00 Regularized Inverse Reinforcement Learning
Wonseok Jeon, Chen-Yang Su, Paul Barde, Thang Doan, Derek Nowrouzezahrai, Joelle Pineau
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 On the geometry of generalization and memorization in deep neural networks
Cory Stephenson, Suchi Padhy, Abhinav Ganesh, Yue Hui, Hanlin Tang, SueYeon Chung
Poster
Mon 17:00 Model Patching: Closing the Subgroup Performance Gap with Data Augmentation
Karan Goel, Albert Gu, Yixuan Li, Christopher Re
Poster
Mon 17:00 Spatio-Temporal Graph Scattering Transform
Chao Pan, Siheng Chen, Antonio Ortega
Poster
Mon 17:00 Contextual Transformation Networks for Online Continual Learning
Quang Pham, Chenghao Liu, Doyen Sahoo, Steven HOI
Poster
Mon 17:00 Taking Notes on the Fly Helps Language Pre-Training
Qiyu Wu, Chen Xing, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu
Poster
Mon 17:00 Regularization Matters in Policy Optimization - An Empirical Study on Continuous Control
Zhuang Liu, Xuanlin Li, Bingyi Kang, trevor darrell
Poster
Mon 17:00 Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning
Tianlong Chen, Zhenyu Zhang, Sijia Liu, Shiyu Chang, Zhangyang Wang
Poster
Mon 17:00 Latent Skill Planning for Exploration and Transfer
Kevin Xie, Homanga Bharadhwaj, Danijar Hafner, Animesh Garg, Florian Shkurti
Oral
Mon 19:00 SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments
Glen Berseth, Daniel Geng, Coline M Devin, Nicholas Rhinehart, Chelsea Finn, Dinesh Jayaraman, Sergey Levine
Oral
Mon 19:15 Contrastive Explanations for Reinforcement Learning via Embedded Self Predictions
Zhengxian Lin, Kin-Ho Lam, Alan Fern
Oral
Mon 19:30 Parrot: Data-Driven Behavioral Priors for Reinforcement Learning
Avi Singh, Huihan Liu, Gaoyue Zhou, Albert Yu, Nicholas Rhinehart, Sergey Levine
Spotlight
Mon 20:28 Fast Geometric Projections for Local Robustness Certification
Aymeric Fromherz, Klas Leino, Matt Fredrikson, Bryan Parno, Corina Pasareanu
Spotlight
Mon 21:36 Graph Convolution with Low-rank Learnable Local Filters
Xiuyuan Cheng, Zichen Miao, Qiang Qiu
Spotlight
Mon 21:46 The Traveling Observer Model: Multi-task Learning Through Spatial Variable Embeddings
Elliot Meyerson, Risto Miikkulainen
Invited Talk
Tue 0:00 Geometric Deep Learning: the Erlangen Programme of ML
Michael Bronstein
Poster
Tue 1:00 Generalized Multimodal ELBO
Thomas Sutter, Imant Daunhawer, Julia E Vogt
Poster
Tue 1:00 Learning Subgoal Representations with Slow Dynamics
Siyuan Li, Lulu Zheng, Jianhao Wang, Chongjie Zhang
Poster
Tue 1:00 Risk-Averse Offline Reinforcement Learning
Núria Armengol Urpí, Sebastian Curi, Andreas Krause
Poster
Tue 1:00 Efficient Certified Defenses Against Patch Attacks on Image Classifiers
Jan Hendrik Metzen, Maksym Yatsura
Poster
Tue 1:00 Intraclass clustering: an implicit learning ability that regularizes DNNs
Simon Carbonnelle, Christophe De Vleeschouwer
Poster
Tue 1:00 Generalization in data-driven models of primary visual cortex
Konstantin-Klemens Lurz, Mohammad Bashiri, Konstantin Willeke, Akshay Jagadish, Eric Wang, Edgar Walker, Santiago Cadena Cadena, Taliah Muhammad, Erick M Cobos, Andreas Tolias, Alexander S Ecker, Fabian Sinz
Poster
Tue 1:00 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 BOIL: Towards Representation Change for Few-shot Learning
Jaehoon Oh, Hyungjun Yoo, ChangHwan Kim, Se-Young Yun
Poster
Tue 1:00 Contemplating Real-World Object Classification
Ali Borji
Poster
Tue 1:00 Do 2D GANs Know 3D Shape? Unsupervised 3D Shape Reconstruction from 2D Image GANs
Xingang Pan, Bo DAI, Ziwei Liu, Chen Change Loy, Ping Luo
Poster
Tue 1:00 Model-based micro-data reinforcement learning: what are the crucial model properties and which model to choose?
Balázs Kégl, Gabriel Hurtado, Albert Thomas
Poster
Tue 1:00 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 Sample-Efficient Automated Deep Reinforcement Learning
Jörg Franke, Gregor Koehler, André Biedenkapp, Frank Hutter
Poster
Tue 1:00 Group Equivariant Conditional Neural Processes
Makoto Kawano, Wataru Kumagai, Akiyoshi Sannai, Yusuke Iwasawa, Yutaka Matsuo
Poster
Tue 1:00 Practical Real Time Recurrent Learning with a Sparse Approximation
Jacob Menick, Erich Elsen, Utku Evci, Simon Osindero, Karen Simonyan, Alex Graves
Poster
Tue 1:00 Monte-Carlo Planning and Learning with Language Action Value Estimates
Youngsoo Jang, Seokin Seo, Jongmin Lee, Kee-Eung Kim
Poster
Tue 1:00 Lossless Compression of Structured Convolutional Models via Lifting
Gustav Sourek, Filip Zelezny, Ondrej Kuzelka
Poster
Tue 1:00 Disambiguating Symbolic Expressions in Informal Documents
Dennis Müller, Cezary Kaliszyk
Poster
Tue 1:00 Neurally Augmented ALISTA
Freya Behrens, Jonathan Sauder, Peter Jung
Poster
Tue 1:00 SkipW: Resource Adaptable RNN with Strict Upper Computational Limit
Tsiry MAYET, Anne Lambert, Pascal Le Guyadec, Francoise Le Bolzer, François Schnitzler
Poster
Tue 1:00 Identifying nonlinear dynamical systems with multiple time scales and long-range dependencies
Dominik Schmidt, Georgia Koppe, Zahra Monfared, Max Beutelspacher, Daniel Durstewitz
Poster
Tue 1:00 Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling
Đorđe Miladinović, Aleksandar Stanić, Stefan Bauer, Jürgen Schmidhuber, Joachim M Buhmann
Poster
Tue 1:00 IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression
Rianne van den Berg, Alexey Gritsenko, Mostafa Dehghani, Casper Sønderby, Tim Salimans
Poster
Tue 1:00 Winning the L2RPN Challenge: Power Grid Management via Semi-Markov Afterstate Actor-Critic
Deunsol Yoon, Sunghoon Hong, Byung-Jun Lee, Kee-Eung Kim
Poster
Tue 1:00 AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models
Ke Sun, Zhanxing Zhu, Zhouchen Lin
Oral
Tue 4:23 Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes
Mike Gartrell, Insu Han, Elvis Dohmatob, Jennifer Gillenwater, Victor-Emmanuel Brunel
Spotlight
Tue 4:38 Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows
Kashif Rasul, Abdul-Saboor Sheikh, Ingmar Schuster, Urs Bergmann, Roland Vollgraf
Tue 5:00 Effect of demographic makeup in covid vaccine administration
Spotlight
Tue 5:08 Mutual Information State Intrinsic Control
Rui Zhao, Yang Gao, Pieter Abbeel, Volker Tresp, Wei Xu
Spotlight
Tue 5:28 Identifying nonlinear dynamical systems with multiple time scales and long-range dependencies
Dominik Schmidt, Georgia Koppe, Zahra Monfared, Max Beutelspacher, Daniel Durstewitz
Tue 6:00 Unstructured Data Challenges in Healthcare (#1)
Poster
Tue 9:00 Transient Non-stationarity and Generalisation in Deep Reinforcement Learning
Maximilian Igl, Gregory Farquhar, Jelena Luketina, Wendelin Boehmer, Shimon Whiteson
Poster
Tue 9:00 Are wider nets better given the same number of parameters?
Anna Golubeva, Guy Gur-Ari, Behnam Neyshabur
Poster
Tue 9:00 Sharper Generalization Bounds for Learning with Gradient-dominated Objective Functions
Yunwen Lei, Yiming Ying
Poster
Tue 9:00 Provable Rich Observation Reinforcement Learning with Combinatorial Latent States
Dipendra Misra, Qinghua Liu, Chi Jin, John Langford
Poster
Tue 9:00 Text Generation by Learning from Demonstrations
Richard Pang, He He
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 Anatomy of Catastrophic Forgetting: Hidden Representations and Task Semantics
Vinay Ramasesh, Ethan Dyer, Maithra Raghu
Poster
Tue 9:00 Clairvoyance: A Pipeline Toolkit for Medical Time Series
Dan Jarrett, Jinsung Yoon, Ioana Bica, Zhaozhi Qian, Ari Ercole, Mihaela van der Schaar
Poster
Tue 9:00 Tradeoffs in Data Augmentation: An Empirical Study
Rapha Gontijo Lopes, Sylvia Smullin, Ekin Cubuk, Ethan Dyer
Poster
Tue 9:00 Data-Efficient Reinforcement Learning with Self-Predictive Representations
Max Schwarzer, Ankesh Anand, Rishab Goel, R Devon Hjelm, Aaron Courville, Philip Bachman
Poster
Tue 9:00 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 Value Functions in Deep Policy Gradients using Residual Variance
Yannis Flet-Berliac, reda ouhamma, odalric-ambrym maillard, philippe preux
Tue 9:00 How to shine in your technical presentation
Poster
Tue 9:00 Statistical inference for individual fairness
Subha Maity, Songkai Xue, Mikhail Yurochkin, Yuekai Sun
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 Recurrent Independent Mechanisms
Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, Bernhard Schoelkopf
Poster
Tue 9:00 Direction Matters: On the Implicit Bias of Stochastic Gradient Descent with Moderate Learning Rate
Jingfeng Wu, Difan Zou, vladimir braverman, Quanquan Gu
Poster
Tue 9:00 Reducing the Computational Cost of Deep Generative Models with Binary Neural Networks
Thomas Bird, Friso Kingma, David Barber
Poster
Tue 9:00 The geometry of integration in text classification RNNs
Kyle Aitken, Vinay Ramasesh, Ankush Garg, Yuan Cao, David Sussillo, Niru Maheswaranathan
Poster
Tue 9:00 Decoupling Global and Local Representations via Invertible Generative Flows
Xuezhe Ma, Xiang Kong, Shanghang Zhang, Eduard H Hovy
Poster
Tue 9:00 Learning Robust State Abstractions for Hidden-Parameter Block MDPs
Amy Zhang, Shagun Sodhani, Khimya Khetarpal, Joelle Pineau
Poster
Tue 9:00 Discovering a set of policies for the worst case reward
Tom Zahavy, Andre Barreto, Daniel J Mankowitz, Shaobo Hou, Brendan ODonoghue, Iurii Kemaev, Satinder Singh
Poster
Tue 9:00 Learning from Protein Structure with Geometric Vector Perceptrons
Bowen Jing, Stephan Eismann, Patricia Suriana, Raphael J Townshend, Ron Dror
Poster
Tue 9:00 Taming GANs with Lookahead-Minmax
Tatjana Chavdarova, Matteo Pagliardini, Sebastian Stich, François Fleuret, Martin Jaggi
Poster
Tue 9:00 Learning Parametrised Graph Shift Operators
George Dasoulas, Johannes Lutzeyer, Michalis Vazirgiannis
Poster
Tue 9:00 DC3: A learning method for optimization with hard constraints
Priya Donti, David Rolnick, Zico Kolter
Poster
Tue 9:00 Representation Learning via Invariant Causal Mechanisms
Jovana Mitrovic, Brian McWilliams, Jacob C Walker, Lars Buesing, Charles Blundell
Poster
Tue 9:00 Unsupervised Object Keypoint Learning using Local Spatial Predictability
Anand Gopalakrishnan, Sjoerd van Steenkiste, Jürgen Schmidhuber
Poster
Tue 9:00 Quantifying Differences in Reward Functions
Adam Gleave, Michael Dennis, Shane Legg, Stuart Russell, Jan Leike
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 How Benign is Benign Overfitting ?
Amartya Sanyal, Puneet Dokania, Varun Kanade, Philip Torr
Poster
Tue 9:00 Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding
Sana Tonekaboni, Danny Eytan, Anna Goldenberg
Poster
Tue 9:00 SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments
Glen Berseth, Daniel Geng, Coline M Devin, Nicholas Rhinehart, Chelsea Finn, Dinesh Jayaraman, Sergey Levine
Poster
Tue 9:00 Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval
Lee Xiong, Chenyan Xiong, Ye Li, Kwok-Fung Tang, Jialin Liu, Paul N Bennett, Junaid Ahmed, Arnold Overwijk
Poster
Tue 9:00 Rank the Episodes: A Simple Approach for Exploration in Procedurally-Generated Environments
Daochen Zha, Wenye Ma, Lei Yuan, Xia Hu, Ji Liu
Poster
Tue 9:00 Vulnerability-Aware Poisoning Mechanism for Online RL with Unknown Dynamics
Yanchao Sun, Da Huo, Furong Huang
Poster
Tue 9:00 Iterative Empirical Game Solving via Single Policy Best Response
Max Smith, Thomas Anthony, Michael Wellman
Poster
Tue 9:00 Rethinking Attention with Performers
Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Richard Song, Georgiana-Andreea Gane, Tamas Sarlos, Peter Hawkins, Jared Q Davis, Afroz Mohiuddin, Lukasz Kaiser, David Belanger, Lucy J Colwell, Adrian Weller
Poster
Tue 9:00 Interpreting Knowledge Graph Relation Representation from Word Embeddings
Carl Allen, Ivana Balazevic, Timothy Hospedales
Poster
Tue 9:00 SSD: A Unified Framework for Self-Supervised Outlier Detection
Vikash Sehwag, Mung Chiang, Prateek Mittal
Oral
Tue 11:15 Learning Generalizable Visual Representations via Interactive Gameplay
Luca Weihs, Ani Kembhavi, Kiana Ehsani, Sarah M Pratt, Winson Han, Alvaro Herrasti, Eric Kolve, Dustin Schwenk, Roozbeh Mottaghi, Ali Farhadi
Spotlight
Tue 11:40 Recurrent Independent Mechanisms
Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, Bernhard Schoelkopf
Oral
Tue 12:00 Randomized Automatic Differentiation
Deniz Oktay, Nick McGreivy, Joshua Aduol, Alex Beatson, Ryan P Adams
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
Spotlight
Tue 12:50 Learning from Protein Structure with Geometric Vector Perceptrons
Bowen Jing, Stephan Eismann, Patricia Suriana, Raphael J Townshend, Ron Dror
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 Linear Mode Connectivity in Multitask and Continual Learning
Seyed Iman Mirzadeh, Mehrdad Farajtabar, Dilan Gorur, Razvan Pascanu, Hassan Ghasemzadeh
Poster
Tue 17:00 Fantastic Four: Differentiable and Efficient Bounds on Singular Values of Convolution Layers
ssingla Singla, Soheil Feizi
Poster
Tue 17:00 Learning to Reach Goals via Iterated Supervised Learning
Dibya Ghosh, Abhishek Gupta, Ashwin D Reddy, Justin Fu, Coline M Devin, Ben Eysenbach, Sergey Levine
Poster
Tue 17:00 Projected Latent Markov Chain Monte Carlo: Conditional Sampling of Normalizing Flows
Chris Cannella, Mohammadreza Soltani, VAHID TAROKH
Poster
Tue 17:00 How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision
Dongkwan Kim, Alice Oh
Poster
Tue 17:00 The Importance of Pessimism in Fixed-Dataset Policy Optimization
Jacob Buckman, Carles Gelada, Marc G Bellemare
Poster
Tue 17:00 Monotonic Kronecker-Factored Lattice
William Bakst, Nobuyuki Morioka, Erez Louidor
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 Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning
Haibo Yang, Minghong Fang, Jia Liu
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 Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth
Thao Nguyen, Maithra Raghu, Simon Kornblith
Poster
Tue 17:00 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 Usable Information and Evolution of Optimal Representations During Training
Michael Kleinman, Alessandro Achille, Daksh Idnani, Jonathan Kao
Poster
Tue 17:00 Large Batch Simulation for Deep Reinforcement Learning
Brennan Shacklett, Erik Wijmans, Aleksei Petrenko, Manolis Savva, Dhruv Batra, Vladlen Koltun, Kayvon Fatahalian
Poster
Tue 17:00 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 Fuzzy Tiling Activations: A Simple Approach to Learning Sparse Representations Online
Yangchen Pan, Kirby Banman, Martha White
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 Behavioral Cloning from Noisy Demonstrations
Fumihiro Sasaki, Ryota Yamashina
Poster
Tue 17:00 A Hypergradient Approach to Robust Regression without Correspondence
Yujia Xie, Yixiu Mao, Simiao Zuo, Hongteng Xu, Xiaojing Ye, Tuo Zhao, Hongyuan Zha
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 Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning
Aviral Kumar, Rishabh Agarwal, Dibya Ghosh, Sergey Levine
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
Oral
Tue 19:55 Global Convergence of Three-layer Neural Networks in the Mean Field Regime
Huy Tuan Pham, Phan-Minh Nguyen
Spotlight
Tue 20:40 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
Invited Talk
Wed 0:00 Perceiving the 3D World from Images and Video
Lourdes Agapito
Poster
Wed 1:00 Neural Delay Differential Equations
Qunxi Zhu, Yao Guo, Wei Lin
Poster
Wed 1:00 Bidirectional Variational Inference for Non-Autoregressive Text-to-Speech
Yoonhyung Lee, JB Shin, Kyomin Jung
Poster
Wed 1:00 Acting in Delayed Environments with Non-Stationary Markov Policies
Esther Derman, Gal Dalal, Shie Mannor
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 New Bounds For Distributed Mean Estimation and Variance Reduction
Peter Davies, Vijaykrishna Gurunathan, Niusha Moshrefi, Saleh Ashkboos, Dan Alistarh
Poster
Wed 1:00 Knowledge distillation via softmax regression representation learning
Jing Yang, Brais Martinez, Adrian Bulat, Georgios Tzimiropoulos
Poster
Wed 1:00 Grounded Language Learning Fast and Slow
Felix Hill, Olivier Tieleman, Tamara von Glehn, Nathaniel Wong, Hamza Merzic, Stephen Clark
Poster
Wed 1:00 FOCAL: Efficient Fully-Offline Meta-Reinforcement Learning via Distance Metric Learning and Behavior Regularization
Lanqing Li, Rui Yang, Dijun Luo
Poster
Wed 1:00 Deep Neural Network Fingerprinting by Conferrable Adversarial Examples
Nils Lukas, Yuxuan Zhang, Florian Kerschbaum
Poster
Wed 1:00 Graph Edit Networks
Benjamin Paassen, Daniele Grattarola, Daniele Zambon, Cesare Alippi, Barbara E Hammer
Poster
Wed 1:00 Negative Data Augmentation
Abhishek Sinha, Kumar Ayush, Jiaming Song, Burak Uzkent, Hongxia Jin, Stefano Ermon
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 Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization
Tatsuya Matsushima, Hiroki Furuta, Yutaka Matsuo, Ofir Nachum, Shixiang Gu
Poster
Wed 1:00 Discovering Diverse Multi-Agent Strategic Behavior via Reward Randomization
Zhenggang Tang, Chao Yu, Boyuan Chen, Huazhe Xu, Xiaolong Wang, Fei Fang, Simon Du, Yu Wang, Yi Wu
Poster
Wed 1:00 Robust Learning of Fixed-Structure Bayesian Networks in Nearly-Linear Time
Yu Cheng, Honghao Lin
Poster
Wed 1:00 Explaining by Imitating: Understanding Decisions by Interpretable Policy Learning
Alihan Hüyük, Dan Jarrett, Cem Tekin, Mihaela van der Schaar
Poster
Wed 1:00 Neural ODE Processes
Alexander Norcliffe, Cristian Bodnar, Ben Day, Jacob Moss, Pietro Liò
Poster
Wed 1:00 Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov Wasserstein
Khai Nguyen, Son Nguyen, Nhat Ho, Tung Pham, Hung Bui
Poster
Wed 1:00 Efficient Continual Learning with Modular Networks and Task-Driven Priors
Tom Veniat, Ludovic Denoyer, Marc'Aurelio Ranzato
Poster
Wed 1:00 A Wigner-Eckart Theorem for Group Equivariant Convolution Kernels
Leon Lang, Maurice Weiler
Poster
Wed 1:00 Learning Task Decomposition with Ordered Memory Policy Network
Yuchen Lu, Yikang Shen, Siyuan Zhou, Aaron Courville, Joshua B Tenenbaum, Chuang Gan
Poster
Wed 1:00 Return-Based Contrastive Representation Learning for Reinforcement Learning
Guoqing Liu, Chuheng Zhang, Li Zhao, Tao Qin, Jinhua Zhu, Li Jian, Nenghai Yu, Tie-Yan Liu
Poster
Wed 1:00 Bag of Tricks for Adversarial Training
Tianyu Pang, Xiao Yang, Yinpeng Dong, Hang Su, Jun Zhu
Oral
Wed 3:15 Rethinking Attention with Performers
Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Richard Song, Georgiana-Andreea Gane, Tamas Sarlos, Peter Hawkins, Jared Q Davis, Afroz Mohiuddin, Lukasz Kaiser, David Belanger, Lucy J Colwell, Adrian Weller
Oral
Wed 3:30 Share or Not? Learning to Schedule Language-Specific Capacity for Multilingual Translation
Biao Zhang, Ankur Bapna, Rico Sennrich, Orhan Firat
Spotlight
Wed 3:45 Support-set bottlenecks for video-text representation learning
Mandela Patrick, Po-Yao Huang, Yuki Asano, Florian Metze, Alexander G Hauptmann, Joao F. Henriques, Andrea Vedaldi
Spotlight
Wed 4:40 Deep Neural Network Fingerprinting by Conferrable Adversarial Examples
Nils Lukas, Yuxuan Zhang, Florian Kerschbaum
Wed 6:00 Panel discussion on model efficiency and quantization
Invited Talk
Wed 8:00 Is My Dataset Biased?
Kate Saenko
Poster
Wed 9:00 On the Bottleneck of Graph Neural Networks and its Practical Implications
Uri Alon, Eran Yahav
Poster
Wed 9:00 Boost then Convolve: Gradient Boosting Meets Graph Neural Networks
Sergei Ivanov, Liudmila Prokhorenkova
Poster
Wed 9:00 Graph Information Bottleneck for Subgraph Recognition
Junchi Yu, Tingyang Xu, Yu Rong, Yatao Bian, Junzhou Huang, Ran He
Poster
Wed 9:00 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 Average-case Acceleration for Bilinear Games and Normal Matrices
Carles Domingo i Enrich, Fabian Pedregosa, Damien Scieur
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 Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF
Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt, Justin Bayer
Poster
Wed 9:00 DeepAveragers: Offline Reinforcement Learning By Solving Derived Non-Parametric MDPs
aayam shrestha, Stefan Lee, Prasad Tadepalli, Alan Fern
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 Anchor & Transform: Learning Sparse Embeddings for Large Vocabularies
Paul Pu Liang, Manzil Zaheer, Yuan Wang, Amr Ahmed
Poster
Wed 9:00 Watch-And-Help: A Challenge for Social Perception and Human-AI Collaboration
Xavier Puig, Tianmin Shu, Shuang Li, Zilin Wang, Andrew Liao, Joshua B Tenenbaum, Sanja Fidler, Antonio Torralba
Poster
Wed 9:00 Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows
Kashif Rasul, Abdul-Saboor Sheikh, Ingmar Schuster, Urs Bergmann, Roland Vollgraf
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 Mastering Atari with Discrete World Models
Danijar Hafner, Timothy Lillicrap, Mohammad Norouzi, Jimmy Ba
Poster
Wed 9:00 Learning to Represent Action Values as a Hypergraph on the Action Vertices
Arash Tavakoli, Mehdi Fatemi, Petar Kormushev
Poster
Wed 9:00 Entropic gradient descent algorithms and wide flat minima
Fabrizio Pittorino, Carlo Lucibello, Christoph Feinauer, Gabriele Perugini, Carlo Baldassi, Elizaveta Demyanenko, Riccardo Zecchina
Poster
Wed 9:00 Few-Shot Bayesian Optimization with Deep Kernel Surrogates
Martin Wistuba, Josif Grabocka
Poster
Wed 9:00 RODE: Learning Roles to Decompose Multi-Agent Tasks
Tonghan Wang, Tarun Gupta, Anuj Mahajan, Bei Peng, Shimon Whiteson, Chongjie Zhang
Poster
Wed 9:00 PC2WF: 3D Wireframe Reconstruction from Raw Point Clouds
Yujia Liu, Stefano D'Aronco, Konrad Schindler, Jan D Wegner
Poster
Wed 9:00 Learning Generalizable Visual Representations via Interactive Gameplay
Luca Weihs, Ani Kembhavi, Kiana Ehsani, Sarah M Pratt, Winson Han, Alvaro Herrasti, Eric Kolve, Dustin Schwenk, Roozbeh Mottaghi, Ali Farhadi
Poster
Wed 9:00 Ask Your Humans: Using Human Instructions to Improve Generalization in Reinforcement Learning
Valerie Chen, Abhinav Gupta, Kenny Marino
Poster
Wed 9:00 Long-tail learning via logit adjustment
Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Himanshu Jain, Andreas Veit, Sanjiv Kumar
Poster
Wed 9:00 Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms
Maruan Al-Shedivat, Jennifer Gillenwater, Eric P Xing, Afshin Rostamizadeh
Poster
Wed 9:00 Chaos of Learning Beyond Zero-sum and Coordination via Game Decompositions
Yun Kuen Cheung, Yixin Tao
Poster
Wed 9:00 Early Stopping in Deep Networks: Double Descent and How to Eliminate it
Reinhard Heckel, Fatih Furkan Yilmaz
Poster
Wed 9:00 Geometry-Aware Gradient Algorithms for Neural Architecture Search
Liam Li, Misha Khodak, Nina Balcan, Ameet Talwalkar
Poster
Wed 9:00 A Gradient Flow Framework For Analyzing Network Pruning
Ekdeep Lubana, Robert Dick
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 OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning
Anurag Ajay, Aviral Kumar, Pulkit Agrawal, Sergey Levine, Ofir Nachum
Poster
Wed 9:00 Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning
Elan Markowitz, Keshav Balasubramanian, Mehrnoosh Mirtaheri, Sami Abu-El-Haija, Bryan Perozzi, Greg Ver Steeg, Aram Galstyan
Poster
Wed 9:00 Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching
Jonas Geiping, Liam H Fowl, Ronny Huang, Wojciech Czaja, Gavin Taylor, Michael Moeller, Tom Goldstein
Poster
Wed 9:00 Probabilistic Numeric Convolutional Neural Networks
Marc Finzi, Roberto Bondesan, Max Welling
Poster
Wed 9:00 Evaluation of Neural Architectures Trained With Square Loss vs Cross-Entropy in Classification Tasks
Like Hui, Misha Belkin
Poster
Wed 9:00 Self-supervised Visual Reinforcement Learning with Object-centric Representations
Andrii Zadaianchuk, Maximilian Seitzer, Georg Martius
Poster
Wed 9:00 TropEx: An Algorithm for Extracting Linear Terms in Deep Neural Networks
Martin Trimmel, Henning Petzka, Cristian Sminchisescu
Poster
Wed 9:00 Anytime Sampling for Autoregressive Models via Ordered Autoencoding
Yilun Xu, Yang Song, Sahaj Garg, Linyuan Gong, Rui Shu, Aditya Grover, Stefano Ermon
Poster
Wed 9:00 Differentiable Trust Region Layers for Deep Reinforcement Learning
Fabian Otto, Philipp Becker, Vien A Ngo, Hanna Ziesche, Gerhard Neumann
Wed 10:00 What can AI researchers do to help prevent Lethal Autonomous Weapons?
Oral
Wed 11:15 Learning to Reach Goals via Iterated Supervised Learning
Dibya Ghosh, Abhishek Gupta, Ashwin D Reddy, Justin Fu, Coline M Devin, Ben Eysenbach, Sergey Levine
Oral
Wed 11:45 Evolving Reinforcement Learning Algorithms
John Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Quoc V Le, Sergey Levine, Honglak Lee, Aleksandra Faust
Spotlight
Wed 12:38 Sequential Density Ratio Estimation for Simultaneous Optimization of Speed and Accuracy
Akinori Ebihara, Taiki Miyagawa, Kazuyuki Sakurai, Hitoshi Imaoka
Spotlight
Wed 12:58 Grounded Language Learning Fast and Slow
Felix Hill, Olivier Tieleman, Tamara von Glehn, Nathaniel Wong, Hamza Merzic, Stephen Clark
Spotlight
Wed 13:18 Unsupervised Object Keypoint Learning using Local Spatial Predictability
Anand Gopalakrishnan, Sjoerd van Steenkiste, Jürgen Schmidhuber
Spotlight
Wed 13:28 VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models
Zhisheng Xiao, Karsten Kreis, Jan Kautz, Arash Vahdat
Spotlight
Wed 13:48 A Gradient Flow Framework For Analyzing Network Pruning
Ekdeep Lubana, Robert Dick
Expo Talk Panel
Wed 14:00 Live Panel - Academics@ Presents: Representation Learning at Amazon
Zahra Matson
Poster
Wed 17:00 Control-Aware Representations for Model-based Reinforcement Learning
Brandon Cui, Yinlam Chow, Mohammad Ghavamzadeh
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 Measuring Massive Multitask Language Understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, Jacob Steinhardt
Poster
Wed 17:00 ALFWorld: Aligning Text and Embodied Environments for Interactive Learning
Mohit Shridhar, Eric Yuan, Marc-Alexandre Cote, Yonatan Bisk, Adam Trischler, Matthew Hausknecht
Poster
Wed 17:00 INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving
Yuhuai Wu, Albert Jiang, Jimmy Ba, Roger Grosse
Poster
Wed 17:00 Combining Physics and Machine Learning for Network Flow Estimation
Arlei Lopes da Silva, Furkan Kocayusufoglu, Saber Jafarpour, Francesco Bullo, Ananthram Swami, Ambuj K Singh
Poster
Wed 17:00 Empirical Analysis of Unlabeled Entity Problem in Named Entity Recognition
Yangming Li, lemao liu, Shuming Shi
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 Wandering within a world: Online contextualized few-shot learning
Mengye Ren, Michael L Iuzzolino, Mike Mozer, Richard Zemel
Poster
Wed 17:00 Efficient Wasserstein Natural Gradients for Reinforcement Learning
Ted Moskovitz, Michael Arbel, Ferenc Huszar, Arthur Gretton
Poster
Wed 17:00 Improved Autoregressive Modeling with Distribution Smoothing
Chenlin Meng, Jiaming Song, Yang Song, Shengjia Zhao, Stefano Ermon
Poster
Wed 17:00 Conservative Safety Critics for Exploration
Homanga Bharadhwaj, Aviral Kumar, Nicholas Rhinehart, Sergey Levine, Florian Shkurti, Animesh Garg
Poster
Wed 17:00 Model-Based Visual Planning with Self-Supervised Functional Distances
Stephen Tian, Suraj Nair, Frederik Ebert, Sudeep Dasari, Ben Eysenbach, Chelsea Finn, Sergey Levine
Poster
Wed 17:00 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 Simple Augmentation Goes a Long Way: ADRL for DNN Quantization
Lin Ning, Guoyang Chen, Weifeng Zhang, Xipeng Shen
Poster
Wed 17:00 GANs Can Play Lottery Tickets Too
Xuxi Chen, Zhenyu Zhang, Yongduo Sui, Tianlong Chen
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 Task-Agnostic Morphology Evolution
Donald Hejna III, Pieter Abbeel, Lerrel Pinto
Poster
Wed 17:00 Learning with Feature-Dependent Label Noise: A Progressive Approach
Yikai Zhang, Songzhu Zheng, Pengxiang Wu, Mayank Goswami, Chao Chen
Poster
Wed 17:00 Evolving Reinforcement Learning Algorithms
John Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Quoc V Le, Sergey Levine, Honglak Lee, Aleksandra Faust
Poster
Wed 17:00 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 Robust Overfitting may be mitigated by properly learned smoothening
Tianlong Chen, Zhenyu Zhang, Sijia Liu, Shiyu Chang, Zhangyang Wang
Poster
Wed 17:00 Fast And Slow Learning Of Recurrent Independent Mechanisms
Kanika Madan, Nan Rosemary Ke, Anirudh Goyal, Bernhard Schoelkopf, Yoshua Bengio
Poster
Wed 17:00 Emergent Symbols through Binding in External Memory
Taylor Webb, Ishan Sinha, Jonathan Cohen
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 Influence Functions in Deep Learning Are Fragile
Samyadeep Basu, Phil Pope, Soheil Feizi
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 Adaptive Procedural Task Generation for Hard-Exploration Problems
Kuan Fang, Yuke Zhu, Silvio Savarese, Li Fei-Fei
Poster
Wed 17:00 gradSim: Differentiable simulation for system identification and visuomotor control
Krishna Murthy Jatavallabhula, Miles Macklin, Florian Golemo, Vikram Voleti, Linda Petrini, Martin Weiss, Breandan Considine, Jérôme Parent-Lévesque, Kevin Xie, Kenny Erleben, Liam Paull, Florian Shkurti, Derek Nowrouzezahrai, Sanja Fidler
Poster
Wed 17:00 Efficient Reinforcement Learning in Factored MDPs with Application to Constrained RL
Xiaoyu Chen, Jiachen Hu, Lihong Li, Liwei Wang
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 Efficient Conformal Prediction via Cascaded Inference with Expanded Admission
Adam Fisch, Tal Schuster, Tommi Jaakkola, Regina Barzilay
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 AdaFuse: Adaptive Temporal Fusion Network for Efficient Action Recognition
Yue Meng, Rameswar Panda, Chung-Ching Lin, Prasanna Sattigeri, Leonid Karlinsky, Kate Saenko, Aude Oliva, Rogerio Feris
Poster
Wed 17:00 A Geometric Analysis of Deep Generative Image Models and Its Applications
Binxu Wang, Carlos Ponce
Oral
Wed 19:00 Improved Autoregressive Modeling with Distribution Smoothing
Chenlin Meng, Jiaming Song, Yang Song, Shengjia Zhao, Stefano Ermon
Spotlight
Wed 19:35 Emergent Symbols through Binding in External Memory
Taylor Webb, Ishan Sinha, Jonathan Cohen
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 21:15 PlasticineLab: A Soft-Body Manipulation Benchmark with Differentiable Physics
Zhiao Huang, Yuanming Hu, Tao Du, Siyuan Zhou, Hao Su, Joshua B Tenenbaum, Chuang Gan
Spotlight
Wed 21:25 Regularization Matters in Policy Optimization - An Empirical Study on Continuous Control
Zhuang Liu, Xuanlin Li, Bingyi Kang, trevor darrell
Spotlight
Wed 21:35 Regularized Inverse Reinforcement Learning
Wonseok Jeon, Chen-Yang Su, Paul Barde, Thang Doan, Derek Nowrouzezahrai, Joelle Pineau
Spotlight
Wed 21:45 Behavioral Cloning from Noisy Demonstrations
Fumihiro Sasaki, Ryota Yamashina
Oral
Thu 0:00 Rethinking Architecture Selection in Differentiable NAS
Ruochen Wang, Minhao Cheng, Xiangning Chen, Xiaocheng Tang, Cho-Jui Hsieh
Poster
Thu 1:00 Balancing Constraints and Rewards with Meta-Gradient D4PG
Dan A. Calian, Daniel J Mankowitz, Tom Zahavy, Zhongwen Xu, Junhyuk Oh, Nir Levine, Timothy A Mann
Poster
Thu 1:00 What Matters for On-Policy Deep Actor-Critic Methods? A Large-Scale Study
Marcin Andrychowicz, Anton Raichuk, Piotr Stanczyk, Manu Orsini, Sertan Girgin, Raphaël Marinier, Hussenot Hussenot-Desenonges, Matthieu Geist, Olivier Pietquin, Marcin Michalski, Sylvain Gelly, Olivier Bachem
Poster
Thu 1:00 Practical Massively Parallel Monte-Carlo Tree Search Applied to Molecular Design
Xiufeng Yang, Tanuj Aasawat, Kazuki Yoshizoe
Poster
Thu 1:00 CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning
Ossama Ahmed, Frederik Träuble, Anirudh Goyal, Alexander Neitz, Manuel Wuthrich, Yoshua Bengio, Bernhard Schoelkopf, Stefan Bauer
Poster
Thu 1:00 Impact of Representation Learning in Linear Bandits
Jiaqi Yang, Wei Hu, Jason Lee, Simon Du
Poster
Thu 1:00 Adversarially Guided Actor-Critic
Yannis Flet-Berliac, Johan Ferret, Olivier Pietquin, philippe preux, Matthieu Geist
Poster
Thu 1:00 Efficient Inference of Flexible Interaction in Spiking-neuron Networks
Feng Zhou, Yixuan Zhang, Jun Zhu
Poster
Thu 1:00 Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks
Yanbang Wang, Yen-Yu Chang, Yunyu Liu, Jure Leskovec, Pan Li
Poster
Thu 1:00 Representation Balancing Offline Model-based Reinforcement Learning
Byung-Jun Lee, Jongmin Lee, Kee-Eung Kim
Poster
Thu 1:00 Hopfield Networks is All You Need
Hubert Ramsauer, Bernhard Schäfl, Johannes Lehner, Philipp Seidl, Michael Widrich, Lukas Gruber, Markus Holzleitner, Thomas Adler, David Kreil, Michael K Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter
Poster
Thu 1:00 Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes
Mike Gartrell, Insu Han, Elvis Dohmatob, Jennifer Gillenwater, Victor-Emmanuel Brunel
Poster
Thu 1:00 Emergent Road Rules In Multi-Agent Driving Environments
Avik Pal, Jonah Philion, Andrew Liao, Sanja Fidler
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 Adaptive Extra-Gradient Methods for Min-Max Optimization and Games
Kimon ANTONAKOPOULOS, E. Belmega, Panayotis Mertikopoulos
Poster
Thu 1:00 AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights
Byeongho Heo, Sanghyuk Chun, Seong Joon Oh, Dongyoon Han, Sangdoo Yun, Gyuwan Kim, Youngjung Uh, Jung-Woo Ha
Poster
Thu 1:00 Private Image Reconstruction from System Side Channels Using Generative Models
Yuanyuan Yuan, Shuai Wang, Junping Zhang
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 Contrastive Divergence Learning is a Time Reversal Adversarial Game
Omer Yair, Tomer Michaeli
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 Learning What To Do by Simulating the Past
David Lindner, Rohin Shah, Pieter Abbeel, Anca Dragan
Poster
Thu 1:00 Kanerva++: Extending the Kanerva Machine With Differentiable, Locally Block Allocated Latent Memory
Jason Ramapuram, Yan Wu, Alexandros Kalousis
Poster
Thu 1:00 Network Pruning That Matters: A Case Study on Retraining Variants
Duong Le, Binh-Son Hua
Poster
Thu 1:00 Genetic Soft Updates for Policy Evolution in Deep Reinforcement Learning
Enrico Marchesini, Davide Corsi, Alessandro Farinelli
Poster
Thu 1:00 Grounding Language to Autonomously-Acquired Skills via Goal Generation
Ahmed Akakzia, Cédric Colas, Pierre-Yves Oudeyer, Mohamed CHETOUANI, Olivier Sigaud
Poster
Thu 1:00 GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding
Dmitry Lepikhin, HyoukJoong Lee, Yuanzhong Xu, Dehao Chen, Orhan Firat, Yanping Huang, Maxim Krikun, Noam Shazeer, Zhifeng Chen
Poster
Thu 1:00 Contrastive Explanations for Reinforcement Learning via Embedded Self Predictions
Zhengxian Lin, Kin-Ho Lam, Alan Fern
Poster
Thu 1:00 Adaptive and Generative Zero-Shot Learning
Yu-Ying Chou, Hsuan-Tien (Tien) Lin, Tyng-Luh Liu
Poster
Thu 1:00 Retrieval-Augmented Generation for Code Summarization via Hybrid GNN
Shangqing Liu, Yu Chen, Xiaofei Xie, Siow Jing Kai, Yang Liu
Oral
Thu 3:00 What Matters for On-Policy Deep Actor-Critic Methods? A Large-Scale Study
Marcin Andrychowicz, Anton Raichuk, Piotr Stanczyk, Manu Orsini, Sertan Girgin, Raphaël Marinier, Hussenot Hussenot-Desenonges, Matthieu Geist, Olivier Pietquin, Marcin Michalski, Sylvain Gelly, Olivier Bachem
Spotlight
Thu 3:15 Winning the L2RPN Challenge: Power Grid Management via Semi-Markov Afterstate Actor-Critic
Deunsol Yoon, Sunghoon Hong, Byung-Jun Lee, Kee-Eung Kim
Spotlight
Thu 3:25 UPDeT: Universal Multi-agent RL via Policy Decoupling with Transformers
Siyi Hu, Fengda Zhu, Xiaojun Chang, Xiaodan Liang
Spotlight
Thu 3:35 Quantifying Differences in Reward Functions
Adam Gleave, Michael Dennis, Shane Legg, Stuart Russell, Jan Leike
Spotlight
Thu 3:45 Iterative Empirical Game Solving via Single Policy Best Response
Max Smith, Thomas Anthony, Michael Wellman
Spotlight
Thu 3:55 Discovering a set of policies for the worst case reward
Tom Zahavy, Andre Barreto, Daniel J Mankowitz, Shaobo Hou, Brendan ODonoghue, Iurii Kemaev, Satinder Singh
Spotlight
Thu 4:45 Self-supervised Visual Reinforcement Learning with Object-centric Representations
Andrii Zadaianchuk, Maximilian Seitzer, Georg Martius
Spotlight
Thu 5:05 Retrieval-Augmented Generation for Code Summarization via Hybrid GNN
Shangqing Liu, Yu Chen, Xiaofei Xie, Siow Jing Kai, Yang Liu
Spotlight
Thu 5:15 Practical Real Time Recurrent Learning with a Sparse Approximation
Jacob Menick, Erich Elsen, Utku Evci, Simon Osindero, Karen Simonyan, Alex Graves
Poster
Thu 9:00 Blending MPC & Value Function Approximation for Efficient Reinforcement Learning
Mohak Bhardwaj, Sanjiban Choudhury, Byron Boots
Poster
Thu 9:00 Gradient Vaccine: Investigating and Improving Multi-task Optimization in Massively Multilingual Models
Zirui Wang, Yulia Tsvetkov, Orhan Firat, Yuan Cao
Poster
Thu 9:00 Deconstructing the Regularization of BatchNorm
Yann Dauphin, Ekin Cubuk
Poster
Thu 9:00 C-Learning: Learning to Achieve Goals via Recursive Classification
Ben Eysenbach, Ruslan Salakhutdinov, Sergey Levine
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 Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning
Rishabh Agarwal, Marlos C. Machado, Pablo Samuel Castro, Marc G Bellemare
Poster
Thu 9:00 BREEDS: Benchmarks for Subpopulation Shift
Shibani Santurkar, Dimitris Tsipras, Aleksander Madry
Thu 9:00 Bad hypothesis contest
Poster
Thu 9:00 Lifelong Learning of Compositional Structures
Jorge Mendez, ERIC EATON
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 Hierarchical Reinforcement Learning by Discovering Intrinsic Options
Jesse Zhang, Haonan Yu, Wei Xu
Poster
Thu 9:00 Correcting experience replay for multi-agent communication
Sanjeevan Ahilan, Peter Dayan
Poster
Thu 9:00 Neural Learning of One-of-Many Solutions for Combinatorial Problems in Structured Output Spaces
Yatin Nandwani, Deepanshu Jindal, Mausam ., Parag Singla
Poster
Thu 9:00 Enforcing robust control guarantees within neural network policies
Priya Donti, Melrose Roderick, Mahyar Fazlyab, Zico Kolter
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 A Mathematical Exploration of Why Language Models Help Solve Downstream Tasks
Nikunj Saunshi, Sadhika Malladi, Sanjeev Arora
Poster
Thu 9:00 Model-Based Offline Planning
Arthur Argenson, Gabe Dulac-Arnold
Poster
Thu 9:00 Directed Acyclic Graph Neural Networks
Veronika Thost, Jie Chen
Poster
Thu 9:00 Learning to Recombine and Resample Data For Compositional Generalization
Ekin Akyürek, Afra Feyza Akyürek, Jacob Andreas
Poster
Thu 9:00 A Critique of Self-Expressive Deep Subspace Clustering
Ben Haeffele, Chong You, Rene Vidal
Poster
Thu 9:00 Efficient Transformers in Reinforcement Learning using Actor-Learner Distillation
Emilio Parisotto, Ruslan Salakhutdinov
Poster
Thu 9:00 Robust early-learning: Hindering the memorization of noisy labels
Xiaobo Xia, Tongliang Liu, Bo Han, Chen Gong, Nannan Wang, Zongyuan Ge, Yi Chang
Oral
Thu 11:30 When Do Curricula Work?
Xiaoxia (Shirley) Wu, Ethan Dyer, Behnam Neyshabur
Thu 12:00 Philosophy and AGI (#2)
Spotlight
Thu 12:10 Correcting experience replay for multi-agent communication
Sanjeevan Ahilan, Peter Dayan
Spotlight
Thu 12:20 Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning
Rishabh Agarwal, Marlos C. Machado, Pablo Samuel Castro, Marc G Bellemare
Spotlight
Thu 12:30 DeepAveragers: Offline Reinforcement Learning By Solving Derived Non-Parametric MDPs
aayam shrestha, Stefan Lee, Prasad Tadepalli, Alan Fern
Spotlight
Thu 12:40 Data-Efficient Reinforcement Learning with Self-Predictive Representations
Max Schwarzer, Ankesh Anand, Rishab Goel, R Devon Hjelm, Aaron Courville, Philip Bachman
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
Thu 14:00 Social AI Virtual Gathering
Invited Talk
Thu 16:00 Self-Supervision for Learning from the Bottom Up
Alyosha Efros
Poster
Thu 17:00 Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers
Kaidi Xu, Huan Zhang, Shiqi Wang, Yihan Wang, Suman Jana, Xue Lin, Cho-Jui Hsieh
Poster
Thu 17:00 Factorizing Declarative and Procedural Knowledge in Structured, Dynamical Environments
Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Charles Blundell, Sergey Levine, Yoshua Bengio, Mike Mozer
Poster
Thu 17:00 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 Greedy-GQ with Variance Reduction: Finite-time Analysis and Improved Complexity
Shaocong Ma, Ziyi Chen, Yi Zhou, Shaofeng Zou
Poster
Thu 17:00 When Do Curricula Work?
Xiaoxia (Shirley) Wu, Ethan Dyer, Behnam Neyshabur
Poster
Thu 17:00 BiPointNet: Binary Neural Network for Point Clouds
Haotong Qin, Zhongang Cai, Mingyuan Zhang, Yifu Ding, Haiyu Zhao, Shuai Yi, Xianglong Liu, Hao Su
Poster
Thu 17:00 Neural Thompson Sampling
Weitong ZHANG, Dongruo Zhou, Lihong Li, Quanquan Gu
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 Theoretical Analysis of Self-Training with Deep Networks on Unlabeled Data
Colin Wei, Kendrick Shen, Yining Chen, Tengyu Ma
Poster
Thu 17:00 Non-asymptotic Confidence Intervals of Off-policy Evaluation: Primal and Dual Bounds
Yihao Feng, Ziyang Tang, Na Zhang, Qiang Liu
Poster
Thu 17:00 Multi-timescale Representation Learning in LSTM Language Models
Shivangi Mahto, Vy Vo, Javier Turek, Alexander Huth
Poster
Thu 17:00 Learning Energy-Based Generative Models via Coarse-to-Fine Expanding and Sampling
Yang Zhao, Jianwen Xie, Ping Li
Poster
Thu 17:00 Molecule Optimization by Explainable Evolution
Binghong Chen, Tianzhe Wang, Chengtao Li, Hanjun Dai, Le Song
Poster
Thu 17:00 Global Convergence of Three-layer Neural Networks in the Mean Field Regime
Huy Tuan Pham, Phan-Minh Nguyen
Poster
Thu 17:00 Learning to Sample with Local and Global Contexts in Experience Replay Buffer
Youngmin Oh, Kimin Lee, Jinwoo Shin, Eunho Yang, Sung Ju Hwang
Poster
Thu 17:00 HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients
Enmao Diao, Jie Ding, VAHID TAROKH
Poster
Thu 17:00 Linear Convergent Decentralized Optimization with Compression
Xiaorui Liu, Yao Li, Rongrong Wang, Jiliang Tang, Ming Yan
Poster
Thu 17:00 Representing Partial Programs with Blended Abstract Semantics
Maxwell Nye, Yewen Pu, Matthew Bowers, Jacob Andreas, Joshua B Tenenbaum, Armando Solar-Lezama
Poster
Thu 17:00 Stochastic Security: Adversarial Defense Using Long-Run Dynamics of Energy-Based Models
Mitch Hill, Jonathan Mitchell, Song-Chun Zhu
Poster
Thu 17:00 Randomized Automatic Differentiation
Deniz Oktay, Nick McGreivy, Joshua Aduol, Alex Beatson, Ryan P Adams
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 Generalization bounds via distillation
Daniel Hsu, Ziwei Ji, Matus Telgarsky, Lan Wang
Poster
Thu 17:00 Evaluation of Similarity-based Explanations
Kazuaki Hanawa, Sho Yokoi, Satoshi Hara, Kentaro Inui
Poster
Thu 17:00 Self-supervised Learning from a Multi-view Perspective
Yao-Hung Hubert Tsai, Yue Wu, Ruslan Salakhutdinov, LP Morency
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 Combining Ensembles and Data Augmentation Can Harm Your Calibration
Yeming Wen, Ghassen Jerfel, Rafael Müller, Michael W Dusenberry, Jasper Snoek, Balaji Lakshminarayanan, Dustin Tran
Poster
Thu 17:00 The Recurrent Neural Tangent Kernel
Sina Alemohammad, Jack Wang, Randall Balestriero, Richard Baraniuk
Poster
Thu 17:00 Adapting to Reward Progressivity via Spectral Reinforcement Learning
Michael Dann, John Thangarajah
Poster
Thu 17:00 Fast Geometric Projections for Local Robustness Certification
Aymeric Fromherz, Klas Leino, Matt Fredrikson, Bryan Parno, Corina Pasareanu
Poster
Thu 17:00 Learning perturbation sets for robust machine learning
Eric Wong, Zico Kolter
Poster
Thu 17:00 MARS: Markov Molecular Sampling for Multi-objective Drug Discovery
Yutong Xie, Chence Shi, Hao Zhou, Yuwei Yang, Weinan Zhang Zhang, Yong Yu, Lei Li
Oral
Thu 19:00 Theoretical Analysis of Self-Training with Deep Networks on Unlabeled Data
Colin Wei, Kendrick Shen, Yining Chen, Tengyu Ma
Spotlight
Thu 19:25 Self-Supervised Policy Adaptation during Deployment
Nicklas Hansen, Rishabh Jangir, Yu Sun, Guillem Alenyà, Pieter Abbeel, Alyosha Efros, Lerrel Pinto, Xiaolong Wang
Spotlight
Thu 19:35 What are the Statistical Limits of Offline RL with Linear Function Approximation?
Ruosong Wang, Dean Foster, Sham M Kakade
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 21:18 MARS: Markov Molecular Sampling for Multi-objective Drug Discovery
Yutong Xie, Chence Shi, Hao Zhou, Yuwei Yang, Weinan Zhang Zhang, Yong Yu, Lei Li
Workshop
Fri 2:45 Ideas for machine learning from psychology's reproducibility crisis
Samuel J Bell
Workshop
Fri 3:05 Model Selection's Disparate Impact in Real-World Deep Learning Applications
Jessica Forde, A. Feder Cooper
Workshop
Fri 5:00 S2D-OLAD: From shallow to deep, overcoming limited and adverse data
Colin Bellinger, Roberto Corizzo, Vincent Dumoulin, Nathalie Japkowicz
Workshop
Fri 5:00 Geometric and Topological Representation Learning
Guy Wolf, Xiuyuan Cheng, Smita Krishnaswamy, Jure Leskovec, Bastian Rieck, Soledad Villar
Workshop
Fri 5:15 Beyond Static Papers: Rethinking How We Share Scientific Understanding in ML
Krishna Murthy Jatavallabhula, Bhairav Mehta, Tegan Maharaj, Amy Tabb, Khimya Khetarpal, Aditya Kusupati, Anna Rogers, Sara Hooker, Breandan Considine, Devi Parikh, Derek Nowrouzezahrai, Yoshua Bengio
Workshop
Fri 5:25 Spotlight 5: Ruihan Yang et al., Scale Space Flow With Autoregressive Priors
Workshop
Fri 5:50 Energy-Based Models: Current Perspectives, Challenges, and Opportunities
Marc Dymetman, Adji Bousso Dieng, Hady Elsahar, Igor Mordatch, Marc'Aurelio Ranzato
Workshop
Fri 6:00 Welcome + Live Introduction of Fabio Carlucci
Fri 6:00 Unstructured Data Challenges in Healthcare (#2)
Workshop
Fri 6:00 Workshop on Neural Architecture Search
Arber Zela, Aaron Klein, Frank Hutter, Liam Li, Jan Hendrik Metzen, Jovita Lukasik
Workshop
Fri 6:00 Invited talk by Aisha Walcott
Aisha Walcott-Bryant
Workshop
Fri 6:00 A Roadmap to Never-Ending RL
Feryal Behbahani, Khimya Khetarpal, Louis Kirsch, Rose Wang, Annie Xie, Adam White, Doina Precup
Workshop
Fri 6:11 Invited Talk Fabio Carlucci
Fabio Carlucci
Workshop
Fri 6:22 On Adversarial Robustness: A Neural Architecture Search perspective
Chaitanya Devaguptapu
Workshop
Fri 6:30 Data-Efficient Training of Autoencoders for Mildly Non-Linear Problems
Muhammad Al-Digeil
Workshop
Fri 6:30 Break & Poster session 1
Workshop
Fri 6:45 Responsible AI (RAI)
Ahmad Beirami, Emily Black, Krishna Gummadi, Hoda Heidari, Baharan Mirzasoleiman, Meisam Razaviyayn, Joshua Williams
Workshop
Fri 6:46 Q&A Fabio Carlucci
Workshop
Fri 7:00 Workshop on Weakly Supervised Learning
Benjamin Roth, Barbara Plank, Alex Ratner, Katharina Kann, Dietrich Klakow, Michael Hedderich
Workshop
Fri 7:00 Neural Conversational AI: Bridging the Gap Between Research and Real World (NeuCAIR)
Ahmad Beirami, Asli Celikyilmaz, Yun-Nung Chen, Paul Crook, Orianna DeMasi, Stephen Roller, Chinnadhurai Sankar, Joao Sedoc, Zhou Yu
Workshop
Fri 7:00 Interpretable Recommender System With Heterogeneous Information: A Geometric Deep Learning Perspective
Yan Leng
Workshop
Fri 7:00 Generalization beyond the training distribution in brains and machines
Christina Funke, Judith Borowski, Drew Linsley, Xavier Boix
Workshop
Fri 7:04 Poster Spotlight "Overfitting in Bayesian Optimization: an empirical study and early-stopping solution"
Huibin Shen, Anastasia Makarova
Workshop
Fri 7:05 Model Discovery in the Sparse Sampling Regime
Gert-Jan Both, Georges Tod, Remy Kusters
Workshop
Fri 7:10 "Can Machine Learning Revolutionize Healthcare? Synthetic Data may be the Answer" by Mihaela van der Schaar, UCLA
Mihaela van der Schaar
Workshop
Fri 7:45 Workshop on Enormous Language Models: Perspectives and Benchmarks
Colin Raffel, Adam Roberts, Amanda Askell, Daphne Ippolito, Ethan Dyer, Guy Gur-Ari, Jared Kaplan, Jascha Sohl-Dickstein, Katherine Lee, Melanie Subbiah, Sam McCandlish, Tom Brown, William Fedus, Vedant Misra, Ambrose Slone, Daniel Freeman
Workshop
Fri 7:55 ICLR 2021 Workshop on Embodied Multimodal Learning (EML)
Ruohan Gao, Andrew Owens, Dinesh Jayaraman, Yuke Zhu, Jiajun Wu, Kristen Grauman
Workshop
Fri 8:00 Panel discussion w/ Allyson Ettinger, Alona Fyshe, Andrea Martin, Dmitry Krotov, Kimberly Statchenfeld, Josh Tenenbaum
Allyson Ettinger, Alona Fyshe, Andrea E. Martin, Dmitry Krotov, Joshua B Tenenbaum, Kimberly Stachenfeld, Leila Wehbe
Workshop
Fri 8:00 Robust and reliable machine learning in the real world
Di Jin, Eric Wong, Yonatan Belinkov, Kai-Wei Chang, Zhijing Jin, Yanjun Qi, Aditi Raghunathan, Tristan Naumann, Mohit Bansal
Workshop
Fri 8:01 "Generative Models for Image Synthesis" by Jan Kautz, NVIDIA
Jan Kautz
Workshop
Fri 8:03 Data Science to fight against COVID-19 by Nuria Oliver
Nuria Oliver
Workshop
Fri 8:22 Prediction of Tuberculosis using U-Net and segmentation techniques
Dennis Hernando Núñez Fernández
Workshop
Fri 8:29 Detection of COVID-19 Disease using Deep Neural Networks with Ultrasound Imaging
Dennis Hernando Núñez Fernández
Workshop
Fri 8:30 Workshop on Distributed and Private Machine Learning
Fatemeh Mireshghallah, Praneeth Vepakomma, Ayush Chopra, Vivek Sharma, Abhishek Singh, Adam Smith, Ramesh Raskar, Gautam Kamath, Reza Shokri
Workshop
Fri 8:31 Ece Kamar - AI in the Open World: Discovering Blind Spots of AI
Ece Kamar
Workshop
Fri 8:36 Fairly Estimating Socioeconomic Status Under Costly Feature Acquisition
Kush R Varshney
Workshop
Fri 8:45 Machine Learning for Preventing and Combating Pandemics
Pengtao Xie, Xiaodan Liang, Jure Leskovec, Judy Wawira, Jeremy Weiss, Manuel Gomez Rodriguez, Madalina Fiterau, Yueyu Jiang, Leo Celi, Eric P Xing
Workshop
Fri 9:00 Paper Session 1 - Paper 1
Kamyar Ghassemipour
Workshop
Fri 9:05 Assessing Physics Informed Neural Networks in Ocean Modelling and Climate Change Applications
Taco de Wolff, Hugo Carrillo Lincopi, Luis Martí, Nayat Sánchez-Pi
Workshop
Fri 9:30 Coffee/Lunch
Workshop
Fri 9:30 Break & Poster session 2
Workshop
Fri 10:00 Spotlights/Poster Session
Workshop
Fri 10:00 Invited Talk: Shirley Ho
Shirley Ho
Workshop
Fri 10:50 Contributed Talk #3: RECON: Rapid Exploration for Open-World Navigation with Latent Goal Models
Dhruv Shah, Ben Eysenbach, Nicholas Rhinehart, Sergey Levine
Workshop
Fri 11:10 Oral 2: Yangjun Ruan et al., Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding
Yang Yang
Workshop
Fri 11:20 Invited Speaker Heng Ji - InfoSurgeon: Cross-media Weak Supervision for Knowledge-Element Level Fake News Detection
Heng Ji
Workshop
Fri 11:26 Introduction of Kimberley Stachenfeld
Workshop
Fri 11:27 Kimberley Stachenfeld
Kimberly Stachenfeld
Workshop
Fri 11:48 Towards Robustness to Label Noise in Text Classification via Noise Modeling
Siddhant Garg
Workshop
Fri 12:00 Coffee/Lunch
Workshop
Fri 12:00 Poster Session #1
Workshop
Fri 12:38 Q&A Brenden Lake, Kimberley Stachenfeld, Thomas Serre
Workshop
Fri 13:00 Poster Session
Workshop
Fri 14:00 Invited talk by Nicholas Carlini
Workshop
Fri 15:00 Spotlights/Poster Session
Workshop
Fri 17:00 Poster Session #2
Workshop
COMBO: Conservative Offline Model-Based Policy Optimization
Tianhe (Kevin) Yu, Aviral Kumar, Aravind Rajeswaran, Rafael Rafailov, Sergey Levine, Chelsea Finn
Workshop
OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation
Jongmin Lee, Wonseok Jeon, Byung-Jun Lee, Joelle Pineau, Kee-Eung Kim
Workshop
RL for Autonomous Mobile Manipulation with Applications to Room Cleaning
Charles Sun, Coline Devin, Abhishek Gupta, Glen Berseth, Sergey Levine
Workshop
Differentially Private Multi-Task Learning
Shengyuan Hu, Steven Wu, Virginia Smith
Workshop
Fast Inference and Transfer of Compositional Task Structure for Few-shot Task Generalization
Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Izzeddin Gur, Aleksandra Faust, Honglak Lee
Workshop
Persistent Reinforcement Learning via Subgoal Curricula
Archit Sharma, Abhishek Gupta, Karol Hausman, Sergey Levine, Chelsea Finn
Workshop
PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse TD Learning
Angelos Filos, Clare Lyle, Yarin Gal, Sergey Levine, Natasha Jaques, Gregory Farquhar
Workshop
Multi-Task Reinforcement Learning with Context-based Representations
Shagun Sodhani, Amy Zhang, Joelle Pineau
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
On Privacy and Confidentiality of Communications in Organizational Graphs
Masoumeh Shafieinejad, Huseyin Inan, Marcello Hasegawa, Robert Sim
Workshop
MPCLeague: Robust 4-party Computation for Privacy-Preserving Machine Learning
Nishat Koti, Arpita Patra, Ajith Suresh
Workshop
CAUSALLY CONSTRAINED DATA SYNTHESIS FOR PRIVATE DATA RELEASE
Varun Chandrasekaran, Darren Edge, Somesh Jha, Amit Sharma, Cheng Zhang, Shruti Tople
Workshop
Layer-wise Characterization of Latent Information Leakage in Federated Learning
Fan Mo, Anastasia Borovykh, Mohammad Malekzadeh, Hamed Haddadi, Soteris Demetriou
Workshop
Federated Learning's Blessing: FedAvg has Linear Speedup
Zhaonan Qu, Kaixiang Lin, Zhaojian Li, Jiayu Zhou, Zhengyuan Zhou
Workshop
What is Going on Inside Recurrent Meta Reinforcement Learning Agents?
Safa Alver, Doina Precup
Workshop
Reset-Free Reinforcement Learning via Multi-Task Learning: Learning Dexterous Manipulation Behaviors without Human Intervention
Abhishek Gupta, Justin Yu, Vikash Kumar, Tony Zhao, Kelvin Xu, Aaron Rovinsky, Thomas Devlin, Sergey Levine
Workshop
Towards Reinforcement Learning in the Continuing Setting
Abhishek Naik, Zaheer Abbas, Adam White, Rich Sutton