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Expo Workshop
Sun 5:00 Real World RL: Azure Personalizer & Vowpal Wabbit
Sheetal Lahabar, Etienne Kintzler, Mark Rucker, Bogdan Mazoure, Qingyun Wu, Pavithra Srinath, Jack Gerrits, Olga Vrousgou, John Langford, Eduardo Salinas
Tutorial
Mon 8:00 Continual Learning with Deep Architectures
Vincenzo Lomonaco, Irina Rish
Affinity Workshop
Mon 10:25 Spotlights 2
Affinity Workshop
Mon 10:35 Towards Explainable Deep Reinforcement Learning for Traffic Signal Control
Lincoln Schreiber, Gabriel Ramos, Ana Lucia Cetertich Bazzan
Affinity Workshop
Mon 10:45 Minimum-Delay Adaptation in Non-Stationary Reinforcement Learning via Online High-Confidence Change-Point Detection
Lucas Alegre, Ana Lucia Cetertich Bazzan , Bruno C. da Silva
Tutorial
Mon 12:00 Online and non-stochastic control
Elad Hazan, Karan Singh
Tutorial
Mon 12:00 Unsupervised Learning for Reinforcement Learning
Aravind Srinivas, Pieter Abbeel
Affinity Workshop
Mon 15:30 Model Reference Adaptive Control for Online Policy Adaptation and Network Synchronization
Miguel F. Arevalo-Castiblanco, Cesar Uribe, Eduardo Mojica-Nava
Oral Session
Tue 5:00 Deep Reinforcement Learning 2
Oral Session
Tue 5:00 Deep Reinforcement Learning 1
Oral Session
Tue 5:00 Reinforcement Learning (Multi-agent)
Oral
Tue 5:00 Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot
Joel Z Leibo, Edgar Duenez-Guzman, Sasha Vezhnevets, John Agapiou, Peter Sunehag, Raphael Koster, Jayd Matyas, Charlie Beattie, Igor Mordatch, Thore Graepel
Oral
Tue 5:00 Phasic Policy Gradient
Karl Cobbe, Jacob Hilton, Oleg Klimov, John Schulman
Oral
Tue 5:00 Deeply-Debiased Off-Policy Interval Estimation
Chengchun Shi, Runzhe Wan, Victor Chernozhukov, Rui Song
Spotlight
Tue 5:20 UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning
Tarun Gupta, Anuj Mahajan, Bei Peng, Wendelin Boehmer, Shimon Whiteson
Spotlight
Tue 5:20 Reinforcement Learning with Prototypical Representations
Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto
Spotlight
Tue 5:20 Offline Contextual Bandits with Overparameterized Models
David Brandfonbrener, Will Whitney, Rajesh Ranganath, Joan Bruna
Spotlight
Tue 5:25 Demonstration-Conditioned Reinforcement Learning for Few-Shot Imitation
Christopher Dance, Perez Julien, Théo Cachet
Spotlight
Tue 5:25 Diversity Actor-Critic: Sample-Aware Entropy Regularization for Sample-Efficient Exploration
Seungyul Han, Youngchul Sung
Spotlight
Tue 5:25 A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning
Dong Ki Kim, Miao Liu, Matthew Riemer, Chuangchuang Sun, Marwa Abdulhai, Golnaz Habibi, Sebastian Lopez-Cot, Gerald Tesauro, Jonathan How
Spotlight
Tue 5:30 Multi-Agent Training beyond Zero-Sum with Correlated Equilibrium Meta-Solvers
Luke Marris, Paul Muller, Marc Lanctot, Karl Tuyls, Thore Graepel
Spotlight
Tue 5:30 Bias-Robust Bayesian Optimization via Dueling Bandits
Johannes Kirschner, Andreas Krause
Spotlight
Tue 5:30 A New Representation of Successor Features for Transfer across Dissimilar Environments
Majid Abdolshah, Hung Le, Thommen Karimpanal George, Sunil Gupta, Santu Rana, Svetha Venkatesh
Spotlight
Tue 5:30 Muesli: Combining Improvements in Policy Optimization
Matteo Hessel, Ivo Danihelka, Fabio Viola, Arthur Guez, Simon Schmitt, Laurent Sifre, Theo Weber, David Silver, Hado van Hasselt
Spotlight
Tue 5:35 Unsupervised Learning of Visual 3D Keypoints for Control
Boyuan Chen, Pieter Abbeel, Deepak Pathak
Spotlight
Tue 5:35 PC-MLP: Model-based Reinforcement Learning with Policy Cover Guided Exploration
Yuda Song, Wen Sun
Spotlight
Tue 5:35 Preferential Temporal Difference Learning
Nishanth Anand, Doina Precup
Spotlight
Tue 5:40 Zoo-Tuning: Adaptive Transfer from A Zoo of Models
Yang Shu, Zhi Kou, Zhangjie Cao, Jianmin Wang, Mingsheng Long
Spotlight
Tue 5:40 On the Optimality of Batch Policy Optimization Algorithms
Chenjun Xiao, Yifan Wu, Jincheng Mei, Bo Dai, Tor Lattimore, Lihong Li, Csaba Szepesvari, Dale Schuurmans
Spotlight
Tue 5:40 Imitation by Predicting Observations
Andrew Jaegle, Yury Sulsky, Arun Ahuja, Jake Bruce, Rob Fergus, Greg Wayne
Spotlight
Tue 5:40 Large-Margin Contrastive Learning with Distance Polarization Regularizer
Shuo Chen, Gang Niu, Chen Gong, Jun Li, Jian Yang, Masashi Sugiyama
Spotlight
Tue 5:40 Learning Task Informed Abstractions
Xiang Fu, Ge Yang, Pulkit Agrawal, Tommi Jaakkola
Spotlight
Tue 5:45 State Entropy Maximization with Random Encoders for Efficient Exploration
Younggyo Seo, Lili Chen, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee
Oral
Tue 6:00 Risk-Sensitive Reinforcement Learning with Function Approximation: A Debiasing Approach
Tom Fei, Zhuoran Yang, Zhaoran Wang
Oral Session
Tue 6:00 Reinforcement Learning 1
Spotlight
Tue 6:20 Model-Free Reinforcement Learning: from Clipped Pseudo-Regret to Sample Complexity
Zhang Zihan, Yuan Zhou, Xiangyang Ji
Spotlight
Tue 6:20 Efficient Differentiable Simulation of Articulated Bodies
Yi-Ling Qiao, Junbang Liang, Vladlen Koltun, Ming Lin
Spotlight
Tue 6:25 Neuro-algorithmic Policies Enable Fast Combinatorial Generalization
Marin Vlastelica, Michal Rolinek, Georg Martius
Spotlight
Tue 6:30 PID Accelerated Value Iteration Algorithm
Amir-massoud Farahmand, Mohammad Ghavamzadeh
Spotlight
Tue 6:35 Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks
Eli Meirom, Haggai Maron, Shie Mannor, Gal Chechik
Spotlight
Tue 6:35 Provably Efficient Learning of Transferable Rewards
Alberto Maria Metelli, Giorgia Ramponi, Alessandro Concetti, Marcello Restelli
Spotlight
Tue 6:40 Reinforcement Learning for Cost-Aware Markov Decision Processes
Wesley A Suttle, Kaiqing Zhang, Zhuoran Yang, Ji Liu, David N Kraemer
Spotlight
Tue 6:40 Bayesian Deep Learning via Subnetwork Inference
Erik Daxberger, Eric Nalisnick, James Allingham, Javier Antorán, Jose Miguel Hernandez-Lobato
Oral Session
Tue 7:00 Reinforcement Learning 2
Oral
Tue 7:00 Coach-Player Multi-agent Reinforcement Learning for Dynamic Team Composition
Bo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, Anima Anandkumar
Oral
Tue 7:00 Skill Discovery for Exploration and Planning using Deep Skill Graphs
Akhil Bagaria, Jason Senthil, George Konidaris
Oral
Tue 7:00 Not All Memories are Created Equal: Learning to Forget by Expiring
Sainbayar Sukhbaatar, Dexter JU, Spencer Poff, Stephen Roller, Arthur Szlam, Jason Weston, Angela Fan
Oral Session
Tue 7:00 Reinforcement Learning and Planning 2
Oral Session
Tue 7:00 Reinforcement Learning and Planning 1
Spotlight
Tue 7:20 Revisiting Rainbow: Promoting more insightful and inclusive deep reinforcement learning research
Johan Obando Ceron, Pablo Samuel Castro
Spotlight
Tue 7:20 Learning Routines for Effective Off-Policy Reinforcement Learning
Edoardo Cetin, Oya Celiktutan
Spotlight
Tue 7:20 Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning
Anuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Anima Anandkumar
Spotlight
Tue 7:25 PODS: Policy Optimization via Differentiable Simulation
Miguel Angel Zamora Mora, Momchil Peychev, Sehoon Ha, Martin Vechev, Stelian Coros
Spotlight
Tue 7:25 A New Formalism, Method and Open Issues for Zero-Shot Coordination
Johannes Treutlein, Michael Dennis, Caspar Oesterheld, Jakob Foerster
Spotlight
Tue 7:25 Deep Reinforcement Learning amidst Continual Structured Non-Stationarity
Annie Xie, James Harrison, Chelsea Finn
Spotlight
Tue 7:30 Targeted Data Acquisition for Evolving Negotiation Agents
Minae Kwon, Sidd Karamcheti, Mariano-Florentino Cuellar, Dorsa Sadigh
Spotlight
Tue 7:30 Offline Reinforcement Learning with Pseudometric Learning
Robert Dadashi, Shideh Rezaeifar, Nino Vieillard, Léonard Hussenot, Olivier Pietquin, Matthieu Geist
Spotlight
Tue 7:30 Learning and Planning in Complex Action Spaces
Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Amin Barekatain, Simon Schmitt, David Silver
Spotlight
Tue 7:35 EMaQ: Expected-Max Q-Learning Operator for Simple Yet Effective Offline and Online RL
Seyed Kamyar Seyed Ghasemipour, Dale Schuurmans, Shixiang Gu
Spotlight
Tue 7:35 Inverse Constrained Reinforcement Learning
Shehryar Malik, Usman Anwar, Alireza Aghasi, Ali Ahmed
Spotlight
Tue 7:35 Model-Based Reinforcement Learning via Latent-Space Collocation
Oleg Rybkin, Chuning Zhu, Anusha Nagabandi, Kostas Daniilidis, Igor Mordatch, Sergey Levine
Spotlight
Tue 7:40 Vector Quantized Models for Planning
Sherjil Ozair, Yazhe Li, Ali Razavi, Ioannis Antonoglou, Aäron van den Oord, Oriol Vinyals
Spotlight
Tue 7:40 Counterfactual Credit Assignment in Model-Free Reinforcement Learning
Thomas Mesnard, Theo Weber, Fabio Viola, Shantanu Thakoor, Alaa Saade, Anna Harutyunyan, Will Dabney, Thomas Stepleton, Nicolas Heess, Arthur Guez, Eric Moulines, Marcus Hutter, Lars Buesing, Remi Munos
Spotlight
Tue 7:45 Interactive Learning from Activity Description
Khanh Nguyen, Dipendra Misra, Robert Schapire, Miro Dudik, Patrick Shafto
Spotlight
Tue 7:45 LTL2Action: Generalizing LTL Instructions for Multi-Task RL
Pashootan Vaezipoor, Andrew C Li, Rodrigo A Toro Icarte, Sheila McIlraith
Spotlight
Tue 7:45 Improved Denoising Diffusion Probabilistic Models
Alexander Nichol, Prafulla Dhariwal
Poster
Tue 9:00 A New Formalism, Method and Open Issues for Zero-Shot Coordination
Johannes Treutlein, Michael Dennis, Caspar Oesterheld, Jakob Foerster
Poster
Tue 9:00 UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning
Tarun Gupta, Anuj Mahajan, Bei Peng, Wendelin Boehmer, Shimon Whiteson
Poster
Tue 9:00 Preferential Temporal Difference Learning
Nishanth Anand, Doina Precup
Poster
Tue 9:00 Imitation by Predicting Observations
Andrew Jaegle, Yury Sulsky, Arun Ahuja, Jake Bruce, Rob Fergus, Greg Wayne
Poster
Tue 9:00 Diversity Actor-Critic: Sample-Aware Entropy Regularization for Sample-Efficient Exploration
Seungyul Han, Youngchul Sung
Poster
Tue 9:00 Offline Reinforcement Learning with Pseudometric Learning
Robert Dadashi, Shideh Rezaeifar, Nino Vieillard, Léonard Hussenot, Olivier Pietquin, Matthieu Geist
Poster
Tue 9:00 Model-Based Reinforcement Learning via Latent-Space Collocation
Oleg Rybkin, Chuning Zhu, Anusha Nagabandi, Kostas Daniilidis, Igor Mordatch, Sergey Levine
Poster
Tue 9:00 A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning
Dong Ki Kim, Miao Liu, Matthew Riemer, Chuangchuang Sun, Marwa Abdulhai, Golnaz Habibi, Sebastian Lopez-Cot, Gerald Tesauro, Jonathan How
Poster
Tue 9:00 Phasic Policy Gradient
Karl Cobbe, Jacob Hilton, Oleg Klimov, John Schulman
Poster
Tue 9:00 Learning and Planning in Complex Action Spaces
Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Amin Barekatain, Simon Schmitt, David Silver
Poster
Tue 9:00 Bias-Robust Bayesian Optimization via Dueling Bandits
Johannes Kirschner, Andreas Krause
Poster
Tue 9:00 PODS: Policy Optimization via Differentiable Simulation
Miguel Angel Zamora Mora, Momchil Peychev, Sehoon Ha, Martin Vechev, Stelian Coros
Poster
Tue 9:00 Demonstration-Conditioned Reinforcement Learning for Few-Shot Imitation
Christopher Dance, Perez Julien, Théo Cachet
Poster
Tue 9:00 Multi-Agent Training beyond Zero-Sum with Correlated Equilibrium Meta-Solvers
Luke Marris, Paul Muller, Marc Lanctot, Karl Tuyls, Thore Graepel
Poster
Tue 9:00 Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot
Joel Z Leibo, Edgar Duenez-Guzman, Sasha Vezhnevets, John Agapiou, Peter Sunehag, Raphael Koster, Jayd Matyas, Charlie Beattie, Igor Mordatch, Thore Graepel
Poster
Tue 9:00 Bayesian Deep Learning via Subnetwork Inference
Erik Daxberger, Eric Nalisnick, James Allingham, Javier Antorán, Jose Miguel Hernandez-Lobato
Poster
Tue 9:00 Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks
Eli Meirom, Haggai Maron, Shie Mannor, Gal Chechik
Poster
Tue 9:00 Reinforcement Learning with Prototypical Representations
Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto
Poster
Tue 9:00 Zoo-Tuning: Adaptive Transfer from A Zoo of Models
Yang Shu, Zhi Kou, Zhangjie Cao, Jianmin Wang, Mingsheng Long
Poster
Tue 9:00 State Entropy Maximization with Random Encoders for Efficient Exploration
Younggyo Seo, Lili Chen, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee
Poster
Tue 9:00 Model-Free Reinforcement Learning: from Clipped Pseudo-Regret to Sample Complexity
Zhang Zihan, Yuan Zhou, Xiangyang Ji
Poster
Tue 9:00 Deep Reinforcement Learning amidst Continual Structured Non-Stationarity
Annie Xie, James Harrison, Chelsea Finn
Poster
Tue 9:00 Offline Contextual Bandits with Overparameterized Models
David Brandfonbrener, Will Whitney, Rajesh Ranganath, Joan Bruna
Poster
Tue 9:00 Counterfactual Credit Assignment in Model-Free Reinforcement Learning
Thomas Mesnard, Theo Weber, Fabio Viola, Shantanu Thakoor, Alaa Saade, Anna Harutyunyan, Will Dabney, Thomas Stepleton, Nicolas Heess, Arthur Guez, Eric Moulines, Marcus Hutter, Lars Buesing, Remi Munos
Poster
Tue 9:00 Deeply-Debiased Off-Policy Interval Estimation
Chengchun Shi, Runzhe Wan, Victor Chernozhukov, Rui Song
Poster
Tue 9:00 Interactive Learning from Activity Description
Khanh Nguyen, Dipendra Misra, Robert Schapire, Miro Dudik, Patrick Shafto
Poster
Tue 9:00 Large-Margin Contrastive Learning with Distance Polarization Regularizer
Shuo Chen, Gang Niu, Chen Gong, Jun Li, Jian Yang, Masashi Sugiyama
Poster
Tue 9:00 On the Optimality of Batch Policy Optimization Algorithms
Chenjun Xiao, Yifan Wu, Jincheng Mei, Bo Dai, Tor Lattimore, Lihong Li, Csaba Szepesvari, Dale Schuurmans
Poster
Tue 9:00 Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning
Anuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Anima Anandkumar
Poster
Tue 9:00 PID Accelerated Value Iteration Algorithm
Amir-massoud Farahmand, Mohammad Ghavamzadeh
Poster
Tue 9:00 Coach-Player Multi-agent Reinforcement Learning for Dynamic Team Composition
Bo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, Anima Anandkumar
Poster
Tue 9:00 Unsupervised Learning of Visual 3D Keypoints for Control
Boyuan Chen, Pieter Abbeel, Deepak Pathak
Poster
Tue 9:00 PC-MLP: Model-based Reinforcement Learning with Policy Cover Guided Exploration
Yuda Song, Wen Sun
Poster
Tue 9:00 Inverse Constrained Reinforcement Learning
Shehryar Malik, Usman Anwar, Alireza Aghasi, Ali Ahmed
Poster
Tue 9:00 Muesli: Combining Improvements in Policy Optimization
Matteo Hessel, Ivo Danihelka, Fabio Viola, Arthur Guez, Simon Schmitt, Laurent Sifre, Theo Weber, David Silver, Hado van Hasselt
Poster
Tue 9:00 EMaQ: Expected-Max Q-Learning Operator for Simple Yet Effective Offline and Online RL
Seyed Kamyar Seyed Ghasemipour, Dale Schuurmans, Shixiang Gu
Poster
Tue 9:00 Learning Task Informed Abstractions
Xiang Fu, Ge Yang, Pulkit Agrawal, Tommi Jaakkola
Poster
Tue 9:00 Vector Quantized Models for Planning
Sherjil Ozair, Yazhe Li, Ali Razavi, Ioannis Antonoglou, Aäron van den Oord, Oriol Vinyals
Poster
Tue 9:00 Provably Efficient Learning of Transferable Rewards
Alberto Maria Metelli, Giorgia Ramponi, Alessandro Concetti, Marcello Restelli
Poster
Tue 9:00 Improved Denoising Diffusion Probabilistic Models
Alexander Nichol, Prafulla Dhariwal
Poster
Tue 9:00 Reinforcement Learning for Cost-Aware Markov Decision Processes
Wesley A Suttle, Kaiqing Zhang, Zhuoran Yang, Ji Liu, David N Kraemer
Poster
Tue 9:00 Skill Discovery for Exploration and Planning using Deep Skill Graphs
Akhil Bagaria, Jason Senthil, George Konidaris
Poster
Tue 9:00 Neuro-algorithmic Policies Enable Fast Combinatorial Generalization
Marin Vlastelica, Michal Rolinek, Georg Martius
Poster
Tue 9:00 Learning Routines for Effective Off-Policy Reinforcement Learning
Edoardo Cetin, Oya Celiktutan
Poster
Tue 9:00 A New Representation of Successor Features for Transfer across Dissimilar Environments
Majid Abdolshah, Hung Le, Thommen Karimpanal George, Sunil Gupta, Santu Rana, Svetha Venkatesh
Poster
Tue 9:00 Decoupling Value and Policy for Generalization in Reinforcement Learning
Roberta Raileanu, Rob Fergus
Poster
Tue 9:00 Risk-Sensitive Reinforcement Learning with Function Approximation: A Debiasing Approach
Tom Fei, Zhuoran Yang, Zhaoran Wang
Poster
Tue 9:00 Not All Memories are Created Equal: Learning to Forget by Expiring
Sainbayar Sukhbaatar, Dexter JU, Spencer Poff, Stephen Roller, Arthur Szlam, Jason Weston, Angela Fan
Poster
Tue 9:00 Efficient Differentiable Simulation of Articulated Bodies
Yi-Ling Qiao, Junbang Liang, Vladlen Koltun, Ming Lin
Poster
Tue 9:00 Revisiting Rainbow: Promoting more insightful and inclusive deep reinforcement learning research
Johan Obando Ceron, Pablo Samuel Castro
Poster
Tue 9:00 Targeted Data Acquisition for Evolving Negotiation Agents
Minae Kwon, Sidd Karamcheti, Mariano-Florentino Cuellar, Dorsa Sadigh
Poster
Tue 9:00 LTL2Action: Generalizing LTL Instructions for Multi-Task RL
Pashootan Vaezipoor, Andrew C Li, Rodrigo A Toro Icarte, Sheila McIlraith
Oral Session
Tue 17:00 Reinforcement Learning and Planning 3
Oral
Tue 17:00 Robust Asymmetric Learning in POMDPs
Andrew Warrington, Jonathan Lavington, Adam Scibior, Mark Schmidt, Frank Wood
Oral Session
Tue 17:00 Reinforcement Learning 3
Oral Session
Tue 17:00 Reinforcement Learning 4
Oral
Tue 17:00 Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning
Shariq Iqbal, Christian Schroeder, Bei Peng, Wendelin Boehmer, Shimon Whiteson, Fei Sha
Oral
Tue 17:00 PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning
Angelos Filos, Clare Lyle, Yarin Gal, Sergey Levine, Natasha Jaques, Gregory Farquhar
Tue 17:00 Continuing (Non-episodic) RL Problems
Yi Wan
Spotlight
Tue 17:20 Safe Reinforcement Learning with Linear Function Approximation
Sanae Amani, Christos Thrampoulidis, Lin Yang
Spotlight
Tue 17:20 Differentiable Spatial Planning using Transformers
Devendra Singh Chaplot, Deepak Pathak, Jitendra Malik
Spotlight
Tue 17:25 Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks
Sungryull Sohn, Sungtae Lee, Jongwook Choi, Harm van Seijen, Mehdi Fatemi, Honglak Lee
Spotlight
Tue 17:25 Adapting to Delays and Data in Adversarial Multi-Armed Bandits
András György, Pooria Joulani
Spotlight
Tue 17:25 Emergent Social Learning via Multi-agent Reinforcement Learning
Kamal Ndousse, Douglas Eck, Sergey Levine, Natasha Jaques
Spotlight
Tue 17:25 Convex Regularization in Monte-Carlo Tree Search
Tuan Q Dam, Carlo D'Eramo, Jan Peters, Joni Pajarinen
Spotlight
Tue 17:30 From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization
Julien Perolat, Remi Munos, Jean-Baptiste Lespiau, Shayegan Omidshafiei, Mark Rowland, Pedro Ortega, Neil Burch, Thomas Anthony, David Balduzzi, Bart De Vylder, Georgios Piliouras, Marc Lanctot, Karl Tuyls
Spotlight
Tue 17:30 Offline Reinforcement Learning with Fisher Divergence Critic Regularization
Ilya Kostrikov, Rob Fergus, Jonathan Tompson, Ofir Nachum
Spotlight
Tue 17:30 On-Policy Deep Reinforcement Learning for the Average-Reward Criterion
Yiming Zhang, Keith Ross
Spotlight
Tue 17:35 Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills
Yevgen Chebotar, Karol Hausman, Yao Lu, Ted Xiao, Dmitry Kalashnikov, Jacob Varley, Alex Irpan, Benjamin Eysenbach, Ryan C Julian, Chelsea Finn, Sergey Levine
Spotlight
Tue 17:35 Recomposing the Reinforcement Learning Building Blocks with Hypernetworks
Elad Sarafian, Shai Keynan, Sarit Kraus
Spotlight
Tue 17:35 Multi-Task Reinforcement Learning with Context-based Representations
Shagun Sodhani, Amy Zhang, Joelle Pineau
Spotlight
Tue 17:40 High Confidence Generalization for Reinforcement Learning
James Kostas, Yash Chandak, Scott Jordan, Georgios Theocharous, Philip Thomas
Spotlight
Tue 17:40 Trajectory Diversity for Zero-Shot Coordination
Andrei Lupu, Brandon Cui, Hengyuan Hu, Jakob Foerster
Spotlight
Tue 17:40 OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation
Jongmin Lee, Wonseok Jeon, Byung-Jun Lee, Joelle Pineau, Kee-Eung Kim
Spotlight
Tue 17:45 Discovering symbolic policies with deep reinforcement learning
Mikel Landajuela Larma, Brenden Petersen, Sookyung Kim, Claudio Santiago, Ruben Glatt, Nathan Mundhenk, Jacob Pettit, Daniel Faissol
Spotlight
Tue 17:45 FOP: Factorizing Optimal Joint Policy of Maximum-Entropy Multi-Agent Reinforcement Learning
Tianhao Zhang, 岳珩 李, Chen Wang, Guangming Xie, Zongqing Lu
Spotlight
Tue 17:45 Locally Persistent Exploration in Continuous Control Tasks with Sparse Rewards
Susan Amin, Maziar Gomrokchi, Hossein Aboutalebi, Harsh Satija, Doina Precup
Oral Session
Tue 18:00 Reinforcement Learning 5
Oral
Tue 18:00 Decoupling Value and Policy for Generalization in Reinforcement Learning
Roberta Raileanu, Rob Fergus
Oral
Tue 18:00 PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-training
Kimin Lee, Laura Smith, Pieter Abbeel
Oral Session
Tue 18:00 Reinforcement Learning 6
Oral Session
Tue 18:00 Reinforcement Learning 7
Oral
Tue 18:00 The Emergence of Individuality
Jiechuan Jiang, Zongqing Lu
Spotlight
Tue 18:20 Prioritized Level Replay
Minqi Jiang, Edward Grefenstette, Tim Rocktäschel
Spotlight
Tue 18:20 Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning
Yue Wu, Shuangfei Zhai, Nitish Srivastava, Josh M Susskind, Jian Zhang, Russ Salakhutdinov, Hanlin Goh
Spotlight
Tue 18:20 DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
Wei-Fang Sun, Cheng-Kuang Lee, Chun-Yi Lee
Spotlight
Tue 18:25 SECANT: Self-Expert Cloning for Zero-Shot Generalization of Visual Policies
Jim Fan, Guanzhi Wang, De-An Huang, Zhiding Yu, Li Fei-Fei, Yuke Zhu, Anima Anandkumar
Spotlight
Tue 18:25 Keyframe-Focused Visual Imitation Learning
Chuan Wen, Jierui Lin, Jianing Qian, Yang Gao, Dinesh Jayaraman
Spotlight
Tue 18:25 Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning
Sumedh Sontakke, Arash Mehrjou, Laurent Itti, Bernhard Schölkopf
Spotlight
Tue 18:25 From Local to Global Norm Emergence: Dissolving Self-reinforcing Substructures with Incremental Social Instruments
Yiwei Liu, Jiamou Liu, Kaibin Wan, Zhan Qin, Zijian Zhang, Bakhadyr Khoussainov, Liehuang Zhu
Spotlight
Tue 18:30 Learning While Playing in Mean-Field Games: Convergence and Optimality
Qiaomin Xie, Zhuoran Yang, Zhaoran Wang, Andreea Minca
Spotlight
Tue 18:30 Learning and Planning in Average-Reward Markov Decision Processes
Yi Wan, Abhishek Naik, Richard Sutton
Spotlight
Tue 18:30 GMAC: A Distributional Perspective on Actor-Critic Framework
Daniel Nam, Younghoon Kim, Chan Park
Spotlight
Tue 18:35 Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement Learning
Matthieu Zimmer, Claire Glanois, Umer Siddique, Paul Weng
Spotlight
Tue 18:35 Goal-Conditioned Reinforcement Learning with Imagined Subgoals
Elliot Chane-Sane, Cordelia Schmid, Ivan Laptev
Spotlight
Tue 18:35 Towards Better Laplacian Representation in Reinforcement Learning with Generalized Graph Drawing
Kaixin Wang, Kuangqi Zhou, Qixin Zhang, Jie Shao, Bryan Hooi, Jiashi Feng
Spotlight
Tue 18:40 Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment
Philip Ball, Cong Lu, Jack Parker-Holder, Stephen Roberts
Spotlight
Tue 18:40 Probabilistic Sequential Shrinking: A Best Arm Identification Algorithm for Stochastic Bandits with Corruptions
Zixin Zhong, Wang Chi Cheung, Vincent Tan
Spotlight
Tue 18:40 Low-Precision Reinforcement Learning: Running Soft Actor-Critic in Half Precision
Johan Björck, Xiangyu Chen, Christopher De Sa, Carla Gomes, Kilian Weinberger
Spotlight
Tue 18:45 Reinforcement Learning of Implicit and Explicit Control Flow Instructions
Ethan Brooks, Janarthanan Rajendran, Richard Lewis, Satinder Singh
Spotlight
Tue 18:45 Emphatic Algorithms for Deep Reinforcement Learning
Ray Jiang, Tom Zahavy, Zhongwen Xu, Adam White, Matteo Hessel, Charles Blundell, Hado van Hasselt
Oral Session
Tue 19:00 Reinforcement Learning 8
Oral
Tue 19:00 Hyperparameter Selection for Imitation Learning
Léonard Hussenot, Marcin Andrychowicz, Damien Vincent, Robert Dadashi, Anton Raichuk, Sabela Ramos, Nikola Momchev, Sertan Girgin, Raphael Marinier, Lukasz Stafiniak, Emmanuel Orsini, Olivier Bachem, Matthieu Geist, Olivier Pietquin
Oral Session
Tue 19:00 Reinforcement Learning 9
Oral
Tue 19:00 Cooperative Exploration for Multi-Agent Deep Reinforcement Learning
Iou-Jen Liu, Unnat Jain, Raymond Yeh, Alex Schwing
Oral Session
Tue 19:00 Deep Reinforcement Learning 3
Oral
Tue 19:00 Inverse Decision Modeling: Learning Interpretable Representations of Behavior
Daniel Jarrett, Alihan Hüyük, Mihaela van der Schaar
Spotlight
Tue 19:20 On Proximal Policy Optimization's Heavy-tailed Gradients
Saurabh Garg, Joshua Zhanson, Emilio Parisotto, Adarsh Prasad, Zico Kolter, Zachary Lipton, Sivaraman Balakrishnan, Russ Salakhutdinov, Pradeep Ravikumar
Spotlight
Tue 19:20 A Deep Reinforcement Learning Approach to Marginalized Importance Sampling with the Successor Representation
Scott Fujimoto, David Meger, Doina Precup
Spotlight
Tue 19:20 Revisiting Peng's Q($\lambda$) for Modern Reinforcement Learning
Tadashi Kozuno, Yunhao Tang, Mark Rowland, Remi Munos, Steven Kapturowski, Will Dabney, Michal Valko, Dave Abel
Spotlight
Tue 19:25 Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning
Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, Shixiang Gu
Spotlight
Tue 19:25 Monotonic Robust Policy Optimization with Model Discrepancy
yuankun jiang, Chenglin Li, Wenrui Dai, Junni Zou, Hongkai Xiong
Spotlight
Tue 19:25 Learning to Weight Imperfect Demonstrations
Yunke Wang, Chang Xu, Bo Du, Honglak Lee
Spotlight
Tue 19:30 Taylor Expansion of Discount Factors
Yunhao Tang, Mark Rowland, Remi Munos, Michal Valko
Spotlight
Tue 19:30 DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning
Daochen Zha, Jingru Xie, Wenye Ma, Sheng Zhang, Xiangru Lian, Xia Hu, Ji Liu
Spotlight
Tue 19:30 Variational Empowerment as Representation Learning for Goal-Conditioned Reinforcement Learning
Jongwook Choi, Archit Sharma, Honglak Lee, Sergey Levine, Shixiang Gu
Spotlight
Tue 19:35 Generalizable Episodic Memory for Deep Reinforcement Learning
Hao Hu, Jianing Ye, Guangxiang Zhu, Zhizhou Ren, Chongjie Zhang
Spotlight
Tue 19:35 Is Pessimism Provably Efficient for Offline RL?
Ying Jin, Zhuoran Yang, Zhaoran Wang
Spotlight
Tue 19:35 MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning
Kevin Li, Abhishek Gupta, Ashwin D Reddy, Vitchyr Pong, Aurick Zhou, Justin Yu, Sergey Levine
Spotlight
Tue 19:40 Beyond Variance Reduction: Understanding the True Impact of Baselines on Policy Optimization
Wes Chung, Valentin Thomas, Marlos C. Machado, Nicolas Le Roux
Spotlight
Tue 19:40 RRL: Resnet as representation for Reinforcement Learning
Rutav Shah, Vikash Kumar
Spotlight
Tue 19:40 Representation Matters: Offline Pretraining for Sequential Decision Making
Mengjiao Yang, Ofir Nachum
Spotlight
Tue 19:45 Density Constrained Reinforcement Learning
Zengyi Qin, Yuxiao Chen, Chuchu Fan
Spotlight
Tue 19:45 SCC: an efficient deep reinforcement learning agent mastering the game of StarCraft II
Xiangjun Wang, Junxiao SONG, Penghui Qi, Peng Peng, Zhenkun Tang, Wei Zhang, Weimin Li, Xiongjun Pi, Jujie He, Chao Gao, Haitao Long, Quan Yuan
Poster
Tue 21:00 Inverse Decision Modeling: Learning Interpretable Representations of Behavior
Daniel Jarrett, Alihan Hüyük, Mihaela van der Schaar
Poster
Tue 21:00 Multi-Task Reinforcement Learning with Context-based Representations
Shagun Sodhani, Amy Zhang, Joelle Pineau
Poster
Tue 21:00 Recomposing the Reinforcement Learning Building Blocks with Hypernetworks
Elad Sarafian, Shai Keynan, Sarit Kraus
Poster
Tue 21:00 Learning and Planning in Average-Reward Markov Decision Processes
Yi Wan, Abhishek Naik, Richard Sutton
Poster
Tue 21:00 PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-training
Kimin Lee, Laura Smith, Pieter Abbeel
Poster
Tue 21:00 Offline Reinforcement Learning with Fisher Divergence Critic Regularization
Ilya Kostrikov, Rob Fergus, Jonathan Tompson, Ofir Nachum
Poster
Tue 21:00 Learning to Weight Imperfect Demonstrations
Yunke Wang, Chang Xu, Bo Du, Honglak Lee
Poster
Tue 21:00 Robust Asymmetric Learning in POMDPs
Andrew Warrington, Jonathan Lavington, Adam Scibior, Mark Schmidt, Frank Wood
Poster
Tue 21:00 Prioritized Level Replay
Minqi Jiang, Edward Grefenstette, Tim Rocktäschel
Poster
Tue 21:00 Generalizable Episodic Memory for Deep Reinforcement Learning
Hao Hu, Jianing Ye, Guangxiang Zhu, Zhizhou Ren, Chongjie Zhang
Poster
Tue 21:00 High Confidence Generalization for Reinforcement Learning
James Kostas, Yash Chandak, Scott Jordan, Georgios Theocharous, Philip Thomas
Poster
Tue 21:00 Representation Matters: Offline Pretraining for Sequential Decision Making
Mengjiao Yang, Ofir Nachum
Poster
Tue 21:00 From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization
Julien Perolat, Remi Munos, Jean-Baptiste Lespiau, Shayegan Omidshafiei, Mark Rowland, Pedro Ortega, Neil Burch, Thomas Anthony, David Balduzzi, Bart De Vylder, Georgios Piliouras, Marc Lanctot, Karl Tuyls
Poster
Tue 21:00 Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning
Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, Shixiang Gu
Poster
Tue 21:00 Convex Regularization in Monte-Carlo Tree Search
Tuan Q Dam, Carlo D'Eramo, Jan Peters, Joni Pajarinen
Poster
Tue 21:00 Differentiable Spatial Planning using Transformers
Devendra Singh Chaplot, Deepak Pathak, Jitendra Malik
Poster
Tue 21:00 Monotonic Robust Policy Optimization with Model Discrepancy
yuankun jiang, Chenglin Li, Wenrui Dai, Junni Zou, Hongkai Xiong
Poster
Tue 21:00 Goal-Conditioned Reinforcement Learning with Imagined Subgoals
Elliot Chane-Sane, Cordelia Schmid, Ivan Laptev
Poster
Tue 21:00 Emphatic Algorithms for Deep Reinforcement Learning
Ray Jiang, Tom Zahavy, Zhongwen Xu, Adam White, Matteo Hessel, Charles Blundell, Hado van Hasselt
Poster
Tue 21:00 Variational Empowerment as Representation Learning for Goal-Conditioned Reinforcement Learning
Jongwook Choi, Archit Sharma, Honglak Lee, Sergey Levine, Shixiang Gu
Poster
Tue 21:00 DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning
Daochen Zha, Jingru Xie, Wenye Ma, Sheng Zhang, Xiangru Lian, Xia Hu, Ji Liu
Poster
Tue 21:00 Safe Reinforcement Learning with Linear Function Approximation
Sanae Amani, Christos Thrampoulidis, Lin Yang
Poster
Tue 21:00 Discovering symbolic policies with deep reinforcement learning
Mikel Landajuela Larma, Brenden Petersen, Sookyung Kim, Claudio Santiago, Ruben Glatt, Nathan Mundhenk, Jacob Pettit, Daniel Faissol
Poster
Tue 21:00 SECANT: Self-Expert Cloning for Zero-Shot Generalization of Visual Policies
Jim Fan, Guanzhi Wang, De-An Huang, Zhiding Yu, Li Fei-Fei, Yuke Zhu, Anima Anandkumar
Poster
Tue 21:00 A Deep Reinforcement Learning Approach to Marginalized Importance Sampling with the Successor Representation
Scott Fujimoto, David Meger, Doina Precup
Poster
Tue 21:00 Is Pessimism Provably Efficient for Offline RL?
Ying Jin, Zhuoran Yang, Zhaoran Wang
Poster
Tue 21:00 On Proximal Policy Optimization's Heavy-tailed Gradients
Saurabh Garg, Joshua Zhanson, Emilio Parisotto, Adarsh Prasad, Zico Kolter, Zachary Lipton, Sivaraman Balakrishnan, Russ Salakhutdinov, Pradeep Ravikumar
Poster
Tue 21:00 Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning
Sumedh Sontakke, Arash Mehrjou, Laurent Itti, Bernhard Schölkopf
Poster
Tue 21:00 Density Constrained Reinforcement Learning
Zengyi Qin, Yuxiao Chen, Chuchu Fan
Poster
Tue 21:00 Taylor Expansion of Discount Factors
Yunhao Tang, Mark Rowland, Remi Munos, Michal Valko
Poster
Tue 21:00 Emergent Social Learning via Multi-agent Reinforcement Learning
Kamal Ndousse, Douglas Eck, Sergey Levine, Natasha Jaques
Poster
Tue 21:00 PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning
Angelos Filos, Clare Lyle, Yarin Gal, Sergey Levine, Natasha Jaques, Gregory Farquhar
Poster
Tue 21:00 OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation
Jongmin Lee, Wonseok Jeon, Byung-Jun Lee, Joelle Pineau, Kee-Eung Kim
Poster
Tue 21:00 Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement Learning
Matthieu Zimmer, Claire Glanois, Umer Siddique, Paul Weng
Poster
Tue 21:00 DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
Wei-Fang Sun, Cheng-Kuang Lee, Chun-Yi Lee
Poster
Tue 21:00 Towards Better Laplacian Representation in Reinforcement Learning with Generalized Graph Drawing
Kaixin Wang, Kuangqi Zhou, Qixin Zhang, Jie Shao, Bryan Hooi, Jiashi Feng
Poster
Tue 21:00 RRL: Resnet as representation for Reinforcement Learning
Rutav Shah, Vikash Kumar
Poster
Tue 21:00 From Local to Global Norm Emergence: Dissolving Self-reinforcing Substructures with Incremental Social Instruments
Yiwei Liu, Jiamou Liu, Kaibin Wan, Zhan Qin, Zijian Zhang, Bakhadyr Khoussainov, Liehuang Zhu
Poster
Tue 21:00 Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills
Yevgen Chebotar, Karol Hausman, Yao Lu, Ted Xiao, Dmitry Kalashnikov, Jacob Varley, Alex Irpan, Benjamin Eysenbach, Ryan C Julian, Chelsea Finn, Sergey Levine
Poster
Tue 21:00 Cooperative Exploration for Multi-Agent Deep Reinforcement Learning
Iou-Jen Liu, Unnat Jain, Raymond Yeh, Alex Schwing
Poster
Tue 21:00 MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning
Kevin Li, Abhishek Gupta, Ashwin D Reddy, Vitchyr Pong, Aurick Zhou, Justin Yu, Sergey Levine
Poster
Tue 21:00 The Emergence of Individuality
Jiechuan Jiang, Zongqing Lu
Poster
Tue 21:00 Keyframe-Focused Visual Imitation Learning
Chuan Wen, Jierui Lin, Jianing Qian, Yang Gao, Dinesh Jayaraman
Poster
Tue 21:00 Reinforcement Learning of Implicit and Explicit Control Flow Instructions
Ethan Brooks, Janarthanan Rajendran, Richard Lewis, Satinder Singh
Poster
Tue 21:00 SCC: an efficient deep reinforcement learning agent mastering the game of StarCraft II
Xiangjun Wang, Junxiao SONG, Penghui Qi, Peng Peng, Zhenkun Tang, Wei Zhang, Weimin Li, Xiongjun Pi, Jujie He, Chao Gao, Haitao Long, Quan Yuan
Poster
Tue 21:00 Hyperparameter Selection for Imitation Learning
Léonard Hussenot, Marcin Andrychowicz, Damien Vincent, Robert Dadashi, Anton Raichuk, Sabela Ramos, Nikola Momchev, Sertan Girgin, Raphael Marinier, Lukasz Stafiniak, Emmanuel Orsini, Olivier Bachem, Matthieu Geist, Olivier Pietquin
Poster
Tue 21:00 Locally Persistent Exploration in Continuous Control Tasks with Sparse Rewards
Susan Amin, Maziar Gomrokchi, Hossein Aboutalebi, Harsh Satija, Doina Precup
Poster
Tue 21:00 Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning
Yue Wu, Shuangfei Zhai, Nitish Srivastava, Josh M Susskind, Jian Zhang, Russ Salakhutdinov, Hanlin Goh
Poster
Tue 21:00 Probabilistic Sequential Shrinking: A Best Arm Identification Algorithm for Stochastic Bandits with Corruptions
Zixin Zhong, Wang Chi Cheung, Vincent Tan
Poster
Tue 21:00 Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning
Shariq Iqbal, Christian Schroeder, Bei Peng, Wendelin Boehmer, Shimon Whiteson, Fei Sha
Poster
Tue 21:00 FOP: Factorizing Optimal Joint Policy of Maximum-Entropy Multi-Agent Reinforcement Learning
Tianhao Zhang, 岳珩 李, Chen Wang, Guangming Xie, Zongqing Lu
Poster
Tue 21:00 Revisiting Peng's Q($\lambda$) for Modern Reinforcement Learning
Tadashi Kozuno, Yunhao Tang, Mark Rowland, Remi Munos, Steven Kapturowski, Will Dabney, Michal Valko, Dave Abel
Poster
Tue 21:00 Beyond Variance Reduction: Understanding the True Impact of Baselines on Policy Optimization
Wes Chung, Valentin Thomas, Marlos C. Machado, Nicolas Le Roux
Poster
Tue 21:00 Learning While Playing in Mean-Field Games: Convergence and Optimality
Qiaomin Xie, Zhuoran Yang, Zhaoran Wang, Andreea Minca
Poster
Tue 21:00 On-Policy Deep Reinforcement Learning for the Average-Reward Criterion
Yiming Zhang, Keith Ross
Poster
Tue 21:00 Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks
Sungryull Sohn, Sungtae Lee, Jongwook Choi, Harm van Seijen, Mehdi Fatemi, Honglak Lee
Poster
Tue 21:00 Trajectory Diversity for Zero-Shot Coordination
Andrei Lupu, Brandon Cui, Hengyuan Hu, Jakob Foerster
Poster
Tue 21:00 GMAC: A Distributional Perspective on Actor-Critic Framework
Daniel Nam, Younghoon Kim, Chan Park
Poster
Tue 21:00 Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment
Philip Ball, Cong Lu, Jack Parker-Holder, Stephen Roberts
Poster
Tue 21:00 Low-Precision Reinforcement Learning: Running Soft Actor-Critic in Half Precision
Johan Björck, Xiangyu Chen, Christopher De Sa, Carla Gomes, Kilian Weinberger
Oral
Wed 5:00 APS: Active Pretraining with Successor Features
Hao Liu, Pieter Abbeel
Oral
Wed 5:00 Near Optimal Reward-Free Reinforcement Learning
Zhang Zihan, Simon Du, Xiangyang Ji
Oral Session
Wed 5:00 Reinforcement Learning 10
Oral Session
Wed 5:00 Reinforcement Learning 11
Oral
Wed 5:00 Cross-domain Imitation from Observations
Dripta S. Raychaudhuri, Sujoy Paul, Jeroen Vanbaar, Amit Roy-Chowdhury
Spotlight
Wed 5:20 Batch Value-function Approximation with Only Realizability
Tengyang Xie, Nan Jiang
Spotlight
Wed 5:20 SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning
Kimin Lee, Michael Laskin, Aravind Srinivas, Pieter Abbeel
Spotlight
Wed 5:20 Guided Exploration with Proximal Policy Optimization using a Single Demonstration
Gabriele Libardi, Gianni De Fabritiis, Sebastian Dittert
Spotlight
Wed 5:25 Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices
Evan Liu, Aditi Raghunathan, Percy Liang, Chelsea Finn
Spotlight
Wed 5:25 Self-Paced Context Evaluation for Contextual Reinforcement Learning
Theresa Eimer, André Biedenkapp, Frank Hutter, Marius Lindauer
Spotlight
Wed 5:30 Model-Free and Model-Based Policy Evaluation when Causality is Uncertain
David Bruns-Smith
Spotlight
Wed 5:30 Active Feature Acquisition with Generative Surrogate Models
Yang Li, Junier Oliva
Spotlight
Wed 5:30 Unsupervised Skill Discovery with Bottleneck Option Learning
Jaekyeom Kim, Seohong Park, Gunhee Kim
Spotlight
Wed 5:35 Bootstrapping Fitted Q-Evaluation for Off-Policy Inference
Botao Hao, Xiang Ji, Yaqi Duan, Hao Lu, Csaba Szepesvari, Mengdi Wang
Spotlight
Wed 5:35 Characterizing the Gap Between Actor-Critic and Policy Gradient
Junfeng Wen, Saurabh Kumar, Ramki Gummadi, Dale Schuurmans
Spotlight
Wed 5:35 TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL
Clément Romac, Rémy Portelas, Katja Hofmann, Pierre-Yves Oudeyer
Spotlight
Wed 5:40 Bilevel Optimization: Convergence Analysis and Enhanced Design
Kaiyi Ji, Junjie Yang, Yingbin LIANG
Spotlight
Wed 5:40 Spectral Normalisation for Deep Reinforcement Learning: An Optimisation Perspective
Florin Gogianu, Tudor Berariu, Mihaela Rosca, Claudia Clopath, Lucian Busoniu, Razvan Pascanu
Spotlight
Wed 5:40 Grounding Language to Entities and Dynamics for Generalization in Reinforcement Learning
Austin W. Hanjie, Victor Zhong, Karthik Narasimhan
Spotlight
Wed 5:45 Data-efficient Hindsight Off-policy Option Learning
Markus Wulfmeier, Dushyant Rao, Roland Hafner, Thomas Lampe, Abbas Abdolmaleki, Tim Hertweck, Michael Neunert, Dhruva Tirumala Bukkapatnam, Noah Siegel, Nicolas Heess, Martin Riedmiller
Spotlight
Wed 5:45 Accelerating Safe Reinforcement Learning with Constraint-mismatched Baseline Policies
Jimmy Yang, Justinian Rosca, Karthik Narasimhan, Peter Ramadge
Oral
Wed 6:00 Bilinear Classes: A Structural Framework for Provable Generalization in RL
Simon Du, Sham Kakade, Jason Lee, Shachar Lovett, Gaurav Mahajan, Wen Sun, Ruosong Wang
Oral Session
Wed 6:00 Reinforcement Learning 12
Oral Session
Wed 6:00 Reinforcement Learning and Optimization
Oral Session
Wed 6:00 Reinforcement Learning Theory 1
Oral
Wed 6:00 Model-based Reinforcement Learning for Continuous Control with Posterior Sampling
Ying Fan, Yifei Ming
Oral
Wed 6:00 Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions
Shuang Qiu, Xiaohan Wei, Jieping Ye, Zhaoran Wang, Zhuoran Yang
Spotlight
Wed 6:20 Megaverse: Simulating Embodied Agents at One Million Experiences per Second
Aleksei Petrenko, Erik Wijmans, Brennan Shacklett, Vladlen Koltun
Spotlight
Wed 6:20 Principled Exploration via Optimistic Bootstrapping and Backward Induction
Chenjia Bai, Lingxiao Wang, Lei Han, Jianye Hao, Animesh Garg, Peng Liu, Zhaoran Wang
Spotlight
Wed 6:20 Risk Bounds and Rademacher Complexity in Batch Reinforcement Learning
Yaqi Duan, Chi Jin, Zhiyuan Li
Spotlight
Wed 6:25 Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing
Filippos Christianos, Georgios Papoudakis, Arrasy Rahman, Stefano V. Albrecht
Spotlight
Wed 6:25 A Lower Bound for the Sample Complexity of Inverse Reinforcement Learning
Abi Komanduru, Jean Honorio
Spotlight
Wed 6:25 Ensemble Bootstrapping for Q-Learning
Oren Peer, Chen Tessler, Nadav Merlis, Ron Meir
Spotlight
Wed 6:30 Towards Open Ad Hoc Teamwork Using Graph-based Policy Learning
Arrasy Rahman, Niklas Hopner, Filippos Christianos, Stefano V. Albrecht
Spotlight
Wed 6:30 Finite-Sample Analysis of Off-Policy Natural Actor-Critic Algorithm
sajad khodadadian, Zaiwei Chen, Siva Maguluri
Spotlight
Wed 6:30 Reward Identification in Inverse Reinforcement Learning
Kuno Kim, Shivam Garg, Kiran Shiragur, Stefano Ermon
Spotlight
Wed 6:35 A Regret Minimization Approach to Iterative Learning Control
Naman Agarwal, Elad Hazan, Anirudha Majumdar, Karan Singh
Spotlight
Wed 6:35 Off-Belief Learning
Hengyuan Hu, Adam Lerer, Brandon Cui, Luis Pineda, Noam Brown, Jakob Foerster
Spotlight
Wed 6:40 TempoRL: Learning When to Act
André Biedenkapp, Raghu Rajan, Frank Hutter, Marius Lindauer
Spotlight
Wed 6:40 Efficient Performance Bounds for Primal-Dual Reinforcement Learning from Demonstrations
Angeliki Kamoutsi, Goran Banjac, John Lygeros
Spotlight
Wed 6:40 On Reinforcement Learning with Adversarial Corruption and Its Application to Block MDP
Tianhao Wu, Yunchang Yang, Simon Du, Liwei Wang
Spotlight
Wed 6:45 Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning
Sebastian Curi, Ilija Bogunovic, Andreas Krause
Spotlight
Wed 6:45 Kernel-Based Reinforcement Learning: A Finite-Time Analysis
Omar Darwiche Domingues, Pierre Menard, Matteo Pirotta, Emilie Kaufmann, Michal Valko
Spotlight
Wed 6:45 Robust Reinforcement Learning using Least Squares Policy Iteration with Provable Performance Guarantees
Kishan Panaganti, Dileep Kalathil
Spotlight
Wed 6:45 State Relevance for Off-Policy Evaluation
Simon Shen, Jason Ma, Omer Gottesman, Finale Doshi-Velez
Oral
Wed 7:00 The Logical Options Framework
Brandon Araki, Xiao Li, Kiran Vodrahalli, Jonathan DeCastro, Micah Fry, Daniela Rus
Spotlight
Wed 7:00 Instabilities of Offline RL with Pre-Trained Neural Representation
Ruosong Wang, Yifan Wu, Russ Salakhutdinov, Sham Kakade
Oral Session
Wed 7:00 Reinforcement Learning 13
Oral
Wed 7:00 High-dimensional Experimental Design and Kernel Bandits
Romain Camilleri, Kevin Jamieson, Julian Katz-Samuels
Spotlight Session
Wed 7:00 Reinforcement Learning and Bandits
Spotlight
Wed 7:05 Path Planning using Neural A* Search
Ryo Yonetani, Tatsunori Taniai, Mohammadamin Barekatain, Mai Nishimura, Asako Kanezaki
Spotlight
Wed 7:15 Tightening the Dependence on Horizon in the Sample Complexity of Q-Learning
Gen Li, Changxiao Cai, Yuxin Chen, Yuantao Gu, Yuting Wei, Yuejie Chi
Oral
Wed 7:20 On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game
Shuang Qiu, Jieping Ye, Zhaoran Wang, Zhuoran Yang
Spotlight
Wed 7:20 Solving Challenging Dexterous Manipulation Tasks With Trajectory Optimisation and Reinforcement Learning
Henry Charlesworth, Giovanni Montana
Spotlight
Wed 7:20 Dichotomous Optimistic Search to Quantify Human Perception
Julien Audiffren
Spotlight
Wed 7:25 Continuous-time Model-based Reinforcement Learning
Cagatay Yildiz, Markus Heinonen, Harri Lähdesmäki
Spotlight
Wed 7:25 Learning in Nonzero-Sum Stochastic Games with Potentials
David Mguni, Yutong Wu, Yali Du, Yaodong Yang, Ziyi Wang, M. Li, Ying Wen, Joel Jennings, Jun Wang
Spotlight
Wed 7:25 Improved Confidence Bounds for the Linear Logistic Model and Applications to Bandits
Kwang-Sung Jun, Lalit Jain, Blake Mason, Houssam Nassif
Spotlight
Wed 7:30 Stochastic Multi-Armed Bandits with Unrestricted Delay Distributions
Tal Lancewicki, Shahar Segal, Tomer Koren, Yishay Mansour
Spotlight
Wed 7:30 Continuous Coordination As a Realistic Scenario for Lifelong Learning
Hadi Nekoei, Akilesh Badrinaaraayanan, Aaron Courville, Sarath Chandar
Spotlight
Wed 7:35 Best Model Identification: A Rested Bandit Formulation
Leonardo Cella, Massimiliano Pontil, Claudio Gentile
Spotlight
Wed 7:35 Deciding What to Learn: A Rate-Distortion Approach
Dilip Arumugam, Benjamin Van Roy
Spotlight
Wed 7:40 Global Convergence of Policy Gradient for Linear-Quadratic Mean-Field Control/Game in Continuous Time
Weichen Wang, Jiequn Han, Zhuoran Yang, Zhaoran Wang
Spotlight
Wed 7:40 Adversarial Option-Aware Hierarchical Imitation Learning
Mingxuan Jing, Wenbing Huang, Fuchun Sun, Xiaojian Ma, Tao Kong, Chuang Gan, Lei Li
Spotlight
Wed 7:40 No-regret Algorithms for Capturing Events in Poisson Point Processes
Mojmir Mutny, Andreas Krause
Spotlight
Wed 7:45 Parametric Graph for Unimodal Ranking Bandit
CamilleS GAUTHIER, Romaric Gaudel, Elisa Fromont, Boammani Aser Lompo
Spotlight
Wed 7:45 Value Iteration in Continuous Actions, States and Time
Michael Lutter, Shie Mannor, Jan Peters, Dieter Fox, Animesh Garg
Poster
Wed 9:00 Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning
Sebastian Curi, Ilija Bogunovic, Andreas Krause
Poster
Wed 9:00 Bilinear Classes: A Structural Framework for Provable Generalization in RL
Simon Du, Sham Kakade, Jason Lee, Shachar Lovett, Gaurav Mahajan, Wen Sun, Ruosong Wang
Poster
Wed 9:00 Towards Open Ad Hoc Teamwork Using Graph-based Policy Learning
Arrasy Rahman, Niklas Hopner, Filippos Christianos, Stefano V. Albrecht
Poster
Wed 9:00 Instabilities of Offline RL with Pre-Trained Neural Representation
Ruosong Wang, Yifan Wu, Russ Salakhutdinov, Sham Kakade
Poster
Wed 9:00 Batch Value-function Approximation with Only Realizability
Tengyang Xie, Nan Jiang
Poster
Wed 9:00 APS: Active Pretraining with Successor Features
Hao Liu, Pieter Abbeel
Poster
Wed 9:00 Path Planning using Neural A* Search
Ryo Yonetani, Tatsunori Taniai, Mohammadamin Barekatain, Mai Nishimura, Asako Kanezaki
Poster
Wed 9:00 Best Model Identification: A Rested Bandit Formulation
Leonardo Cella, Massimiliano Pontil, Claudio Gentile
Poster
Wed 9:00 Stochastic Multi-Armed Bandits with Unrestricted Delay Distributions
Tal Lancewicki, Shahar Segal, Tomer Koren, Yishay Mansour
Poster
Wed 9:00 Model-based Reinforcement Learning for Continuous Control with Posterior Sampling
Ying Fan, Yifei Ming
Poster
Wed 9:00 Data-efficient Hindsight Off-policy Option Learning
Markus Wulfmeier, Dushyant Rao, Roland Hafner, Thomas Lampe, Abbas Abdolmaleki, Tim Hertweck, Michael Neunert, Dhruva Tirumala Bukkapatnam, Noah Siegel, Nicolas Heess, Martin Riedmiller
Poster
Wed 9:00 Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices
Evan Liu, Aditi Raghunathan, Percy Liang, Chelsea Finn
Poster
Wed 9:00 SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning
Kimin Lee, Michael Laskin, Aravind Srinivas, Pieter Abbeel
Poster
Wed 9:00 Value Iteration in Continuous Actions, States and Time
Michael Lutter, Shie Mannor, Jan Peters, Dieter Fox, Animesh Garg
Poster
Wed 9:00 Finite-Sample Analysis of Off-Policy Natural Actor-Critic Algorithm
sajad khodadadian, Zaiwei Chen, Siva Maguluri
Poster
Wed 9:00 The Logical Options Framework
Brandon Araki, Xiao Li, Kiran Vodrahalli, Jonathan DeCastro, Micah Fry, Daniela Rus
Poster
Wed 9:00 Continuous Coordination As a Realistic Scenario for Lifelong Learning
Hadi Nekoei, Akilesh Badrinaaraayanan, Aaron Courville, Sarath Chandar
Poster
Wed 9:00 State Relevance for Off-Policy Evaluation
Simon Shen, Jason Ma, Omer Gottesman, Finale Doshi-Velez
Poster
Wed 9:00 Risk Bounds and Rademacher Complexity in Batch Reinforcement Learning
Yaqi Duan, Chi Jin, Zhiyuan Li
Poster
Wed 9:00 Model-Free and Model-Based Policy Evaluation when Causality is Uncertain
David Bruns-Smith
Poster
Wed 9:00 Bilevel Optimization: Convergence Analysis and Enhanced Design
Kaiyi Ji, Junjie Yang, Yingbin LIANG
Poster
Wed 9:00 Global Convergence of Policy Gradient for Linear-Quadratic Mean-Field Control/Game in Continuous Time
Weichen Wang, Jiequn Han, Zhuoran Yang, Zhaoran Wang
Poster
Wed 9:00 Cross-domain Imitation from Observations
Dripta S. Raychaudhuri, Sujoy Paul, Jeroen Vanbaar, Amit Roy-Chowdhury
Poster
Wed 9:00 Tightening the Dependence on Horizon in the Sample Complexity of Q-Learning
Gen Li, Changxiao Cai, Yuxin Chen, Yuantao Gu, Yuting Wei, Yuejie Chi
Poster
Wed 9:00 Active Feature Acquisition with Generative Surrogate Models
Yang Li, Junier Oliva
Poster
Wed 9:00 No-regret Algorithms for Capturing Events in Poisson Point Processes
Mojmir Mutny, Andreas Krause
Poster
Wed 9:00 Parametric Graph for Unimodal Ranking Bandit
CamilleS GAUTHIER, Romaric Gaudel, Elisa Fromont, Boammani Aser Lompo
Poster
Wed 9:00 Self-Paced Context Evaluation for Contextual Reinforcement Learning
Theresa Eimer, André Biedenkapp, Frank Hutter, Marius Lindauer
Poster
Wed 9:00 Principled Exploration via Optimistic Bootstrapping and Backward Induction
Chenjia Bai, Lingxiao Wang, Lei Han, Jianye Hao, Animesh Garg, Peng Liu, Zhaoran Wang
Poster
Wed 9:00 Characterizing the Gap Between Actor-Critic and Policy Gradient
Junfeng Wen, Saurabh Kumar, Ramki Gummadi, Dale Schuurmans
Poster
Wed 9:00 On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game
Shuang Qiu, Jieping Ye, Zhaoran Wang, Zhuoran Yang
Poster
Wed 9:00 Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions
Shuang Qiu, Xiaohan Wei, Jieping Ye, Zhaoran Wang, Zhuoran Yang
Poster
Wed 9:00 Spectral Normalisation for Deep Reinforcement Learning: An Optimisation Perspective
Florin Gogianu, Tudor Berariu, Mihaela Rosca, Claudia Clopath, Lucian Busoniu, Razvan Pascanu
Poster
Wed 9:00 High-dimensional Experimental Design and Kernel Bandits
Romain Camilleri, Kevin Jamieson, Julian Katz-Samuels
Poster
Wed 9:00 Robust Reinforcement Learning using Least Squares Policy Iteration with Provable Performance Guarantees
Kishan Panaganti, Dileep Kalathil
Poster
Wed 9:00 On Reinforcement Learning with Adversarial Corruption and Its Application to Block MDP
Tianhao Wu, Yunchang Yang, Simon Du, Liwei Wang
Poster
Wed 9:00 Dichotomous Optimistic Search to Quantify Human Perception
Julien Audiffren
Poster
Wed 9:00 Off-Belief Learning
Hengyuan Hu, Adam Lerer, Brandon Cui, Luis Pineda, Noam Brown, Jakob Foerster
Poster
Wed 9:00 Deciding What to Learn: A Rate-Distortion Approach
Dilip Arumugam, Benjamin Van Roy
Poster
Wed 9:00 A Regret Minimization Approach to Iterative Learning Control
Naman Agarwal, Elad Hazan, Anirudha Majumdar, Karan Singh
Poster
Wed 9:00 Near Optimal Reward-Free Reinforcement Learning
Zhang Zihan, Simon Du, Xiangyang Ji
Poster
Wed 9:00 A Lower Bound for the Sample Complexity of Inverse Reinforcement Learning
Abi Komanduru, Jean Honorio
Poster
Wed 9:00 Adversarial Option-Aware Hierarchical Imitation Learning
Mingxuan Jing, Wenbing Huang, Fuchun Sun, Xiaojian Ma, Tao Kong, Chuang Gan, Lei Li
Poster
Wed 9:00 Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing
Filippos Christianos, Georgios Papoudakis, Arrasy Rahman, Stefano V. Albrecht
Poster
Wed 9:00 TempoRL: Learning When to Act
André Biedenkapp, Raghu Rajan, Frank Hutter, Marius Lindauer
Poster
Wed 9:00 Kernel-Based Reinforcement Learning: A Finite-Time Analysis
Omar Darwiche Domingues, Pierre Menard, Matteo Pirotta, Emilie Kaufmann, Michal Valko
Poster
Wed 9:00 Efficient Performance Bounds for Primal-Dual Reinforcement Learning from Demonstrations
Angeliki Kamoutsi, Goran Banjac, John Lygeros
Poster
Wed 9:00 Continuous-time Model-based Reinforcement Learning
Cagatay Yildiz, Markus Heinonen, Harri Lähdesmäki
Poster
Wed 9:00 Grounding Language to Entities and Dynamics for Generalization in Reinforcement Learning
Austin W. Hanjie, Victor Zhong, Karthik Narasimhan
Poster
Wed 9:00 Unsupervised Skill Discovery with Bottleneck Option Learning
Jaekyeom Kim, Seohong Park, Gunhee Kim
Poster
Wed 9:00 Solving Challenging Dexterous Manipulation Tasks With Trajectory Optimisation and Reinforcement Learning
Henry Charlesworth, Giovanni Montana
Poster
Wed 9:00 Bootstrapping Fitted Q-Evaluation for Off-Policy Inference
Botao Hao, Xiang Ji, Yaqi Duan, Hao Lu, Csaba Szepesvari, Mengdi Wang
Poster
Wed 9:00 Learning in Nonzero-Sum Stochastic Games with Potentials
David Mguni, Yutong Wu, Yali Du, Yaodong Yang, Ziyi Wang, M. Li, Ying Wen, Joel Jennings, Jun Wang
Poster
Wed 9:00 Ensemble Bootstrapping for Q-Learning
Oren Peer, Chen Tessler, Nadav Merlis, Ron Meir
Poster
Wed 9:00 Accelerating Safe Reinforcement Learning with Constraint-mismatched Baseline Policies
Jimmy Yang, Justinian Rosca, Karthik Narasimhan, Peter Ramadge
Poster
Wed 9:00 Reward Identification in Inverse Reinforcement Learning
Kuno Kim, Shivam Garg, Kiran Shiragur, Stefano Ermon
Poster
Wed 9:00 TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL
Clément Romac, Rémy Portelas, Katja Hofmann, Pierre-Yves Oudeyer
Poster
Wed 9:00 Megaverse: Simulating Embodied Agents at One Million Experiences per Second
Aleksei Petrenko, Erik Wijmans, Brennan Shacklett, Vladlen Koltun
Poster
Wed 9:00 Guided Exploration with Proximal Policy Optimization using a Single Demonstration
Gabriele Libardi, Gianni De Fabritiis, Sebastian Dittert
Poster
Wed 9:00 Improved Confidence Bounds for the Linear Logistic Model and Applications to Bandits
Kwang-Sung Jun, Lalit Jain, Blake Mason, Houssam Nassif
Oral
Wed 17:00 Exponential Lower Bounds for Batch Reinforcement Learning: Batch RL can be Exponentially Harder than Online RL
Andrea Zanette
Oral
Wed 17:00 The Symmetry between Arms and Knapsacks: A Primal-Dual Approach for Bandits with Knapsacks
Xiaocheng Li, Chunlin Sun, Yinyu Ye
Oral Session
Wed 17:00 Reinforcement Learning Theory 3
Oral Session
Wed 17:00 Reinforcement Learning Theory 2
Oral
Wed 17:00 UCB Momentum Q-learning: Correcting the bias without forgetting
Pierre MENARD, Omar Darwiche Domingues, Xuedong Shang, Michal Valko
Spotlight
Wed 17:20 Dynamic Planning and Learning under Recovering Rewards
David Simchi-Levi, Zeyu Zheng, Feng Zhu
Spotlight
Wed 17:20 Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping
Dongruo Zhou, Jiafan He, Quanquan Gu
Spotlight
Wed 17:25 Best Arm Identification in Graphical Bilinear Bandits
Geovani Rizk, Albert Thomas, Igor Colin, Rida Laraki, Yann Chevaleyre
Spotlight
Wed 17:25 Confidence-Budget Matching for Sequential Budgeted Learning
Yonathan Efroni, Nadav Merlis, Aadirupa Saha, Shie Mannor
Spotlight
Wed 17:30 Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously
Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang, Xiaojin Zhang
Spotlight
Wed 17:30 Sample Efficient Reinforcement Learning In Continuous State Spaces: A Perspective Beyond Linearity
Dhruv Malik, Aldo Pacchiano, Vishwak Srinivasan, Yuanzhi Li
Spotlight
Wed 17:30 Fast active learning for pure exploration in reinforcement learning
Pierre MENARD, Omar Darwiche Domingues, Anders Jonsson, Emilie Kaufmann, Edouard Leurent, Michal Valko
Spotlight
Wed 17:35 Improved Corruption Robust Algorithms for Episodic Reinforcement Learning
Yifang Chen, Simon Du, Kevin Jamieson
Spotlight
Wed 17:35 Incentivized Bandit Learning with Self-Reinforcing User Preferences
Tianchen Zhou, Jia Liu, Chaosheng Dong, jingyuan deng
Spotlight
Wed 17:35 Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient
Botao Hao, Yaqi Duan, Tor Lattimore, Csaba Szepesvari, Mengdi Wang
Spotlight
Wed 17:35 Leveraging Non-uniformity in First-order Non-convex Optimization
Jincheng Mei, Yue Gao, Bo Dai, Csaba Szepesvari, Dale Schuurmans
Spotlight
Wed 17:40 Approximation Theory Based Methods for RKHS Bandits
Sho Takemori, Masahiro Sato
Spotlight
Wed 17:40 Robust Policy Gradient against Strong Data Corruption
Xuezhou Zhang, Yiding Chen, Jerry Zhu, Wen Sun
Spotlight
Wed 17:45 Dynamic Balancing for Model Selection in Bandits and RL
Ashok Cutkosky, Christoph Dann, Abhimanyu Das, Claudio Gentile, Aldo Pacchiano, Manish Purohit
Spotlight
Wed 17:45 Logarithmic Regret for Reinforcement Learning with Linear Function Approximation
Jiafan He, Dongruo Zhou, Quanquan Gu
Oral
Wed 18:00 Task-Optimal Exploration in Linear Dynamical Systems
Andrew Wagenmaker, Max Simchowitz, Kevin Jamieson
Oral
Wed 18:00 Resource Allocation in Multi-armed Bandit Exploration: Overcoming Sublinear Scaling with Adaptive Parallelism
Brijen Thananjeyan, Kirthevasan Kandasamy, Ion Stoica, Michael Jordan, Ken Goldberg, Joseph E Gonzalez
Oral
Wed 18:00 Cyclically Equivariant Neural Decoders for Cyclic Codes
Xiangyu Chen, Min Ye
Oral
Wed 18:00 Provably Efficient Algorithms for Multi-Objective Competitive RL
Tiancheng Yu, Yi Tian, Jingzhao Zhang, Suvrit Sra
Oral Session
Wed 18:00 Reinforcement Learning Theory 4
Oral Session
Wed 18:00 Reinforcement Learning 14
Spotlight
Wed 18:20 Optimal Streaming Algorithms for Multi-Armed Bandits
Tianyuan Jin, Keke Huang, Jing Tang, Xiaokui Xiao
Spotlight
Wed 18:20 Online Learning in Unknown Markov Games
Yi Tian, Yuanhao Wang, Tiancheng Yu, Suvrit Sra
Spotlight
Wed 18:25 Top-k eXtreme Contextual Bandits with Arm Hierarchy
Rajat Sen, Alexander Rakhlin, Lexing Ying, Rahul Kidambi, Dean Foster, Daniel Hill, Inderjit Dhillon
Spotlight
Wed 18:25 CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee
Tengyu Xu, Yingbin LIANG, Guanghui Lan
Spotlight
Wed 18:25 A Sharp Analysis of Model-based Reinforcement Learning with Self-Play
Qinghua Liu, Tiancheng Yu, Yu Bai, Chi Jin
Spotlight
Wed 18:30 Randomized Exploration in Reinforcement Learning with General Value Function Approximation
Haque Ishfaq, Qiwen Cui, Viet Nguyen, Alex Ayoub, Zhuoran Yang, Zhaoran Wang, Doina Precup, Lin Yang
Spotlight
Wed 18:30 Improved Regret Bounds of Bilinear Bandits using Action Space Analysis
Kyoungseok Jang, Kwang-Sung Jun, Se-Young Yun, Wanmo Kang
Spotlight
Wed 18:30 Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality
Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin LIANG
Spotlight
Wed 18:35 Interaction-Grounded Learning
Tengyang Xie, John Langford, Paul Mineiro, Ida Momennejad
Spotlight
Wed 18:35 Deep Coherent Exploration for Continuous Control
Yijie Zhang, Herke van Hoof
Spotlight
Wed 18:40 Almost Optimal Anytime Algorithm for Batched Multi-Armed Bandits
Tianyuan Jin, Jing Tang, Pan Xu, Keke Huang, Xiaokui Xiao, Quanquan Gu
Spotlight
Wed 18:45 Pure Exploration and Regret Minimization in Matching Bandits
Flore Sentenac, Jialin Yi, Clément Calauzènes, Vianney Perchet, Milan Vojnovic
Oral
Wed 19:00 Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning
Xutong Liu, Jinhang Zuo, Xiaowei Chen, Wei Chen, John C. S. Lui
Oral Session
Wed 19:00 Reinforcement Learning Theory 5
Spotlight
Wed 19:20 Near-Optimal Model-Free Reinforcement Learning in Non-Stationary Episodic MDPs
Weichao Mao, Kaiqing Zhang, Ruihao Zhu, David Simchi-Levi, Tamer Basar
Spotlight
Wed 19:20 A Differentiable Point Process with Its Application to Spiking Neural Networks
Hiroshi Kajino
Spotlight
Wed 19:20 Combinatorial Blocking Bandits with Stochastic Delays
Alexia Atsidakou, Orestis Papadigenopoulos, Soumya Basu, Constantine Caramanis, Sanjay Shakkottai
Spotlight
Wed 19:25 AdaXpert: Adapting Neural Architecture for Growing Data
Shuaicheng Niu, Jiaxiang Wu, Guanghui Xu, Yifan Zhang, Yong Guo, Peilin Zhao, Peng Wang, Mingkui Tan
Spotlight
Wed 19:25 Sparsity-Agnostic Lasso Bandit
Min-hwan Oh, Garud Iyengar, Assaf Zeevi
Spotlight
Wed 19:30 Quantile Bandits for Best Arms Identification
Mengyan Zhang, Cheng Soon Ong
Spotlight
Wed 19:30 Provably Correct Optimization and Exploration with Non-linear Policies
Fei Feng, Wotao Yin, Alekh Agarwal, Lin Yang
Spotlight
Wed 19:35 Safe Reinforcement Learning Using Advantage-Based Intervention
Nolan Wagener, Byron Boots, Ching-An Cheng
Spotlight
Wed 19:35 SAINT-ACC: Safety-Aware Intelligent Adaptive Cruise Control for Autonomous Vehicles Using Deep Reinforcement Learning
Lokesh Chandra Das, Myounggyu Won
Spotlight
Wed 19:35 Beyond $log^2(T)$ regret for decentralized bandits in matching markets
Soumya Basu, Karthik Abinav Sankararaman, Abishek Sankararaman
Spotlight
Wed 19:40 Massively Parallel and Asynchronous Tsetlin Machine Architecture Supporting Almost Constant-Time Scaling
Kuruge Darshana Abeyrathna, Bimal Bhattarai, Morten Goodwin, Saeed Rahimi Gorji, Ole-Christoffer Granmo, Lei Jiao, Rupsa Saha, Rohan Kumar Yadav
Spotlight
Wed 19:40 Robust Pure Exploration in Linear Bandits with Limited Budget
Ayya Alieva, Ashok Cutkosky, Abhimanyu Das
Spotlight
Wed 19:45 Adapting to misspecification in contextual bandits with offline regression oracles
Sanath Kumar Krishnamurthy, Vitor Hadad, Susan Athey
Poster
Wed 21:00 Best Arm Identification in Graphical Bilinear Bandits
Geovani Rizk, Albert Thomas, Igor Colin, Rida Laraki, Yann Chevaleyre
Poster
Wed 21:00 Leveraging Non-uniformity in First-order Non-convex Optimization
Jincheng Mei, Yue Gao, Bo Dai, Csaba Szepesvari, Dale Schuurmans
Poster
Wed 21:00 Safe Reinforcement Learning Using Advantage-Based Intervention
Nolan Wagener, Byron Boots, Ching-An Cheng
Poster
Wed 21:00 Exponential Lower Bounds for Batch Reinforcement Learning: Batch RL can be Exponentially Harder than Online RL
Andrea Zanette
Poster
Wed 21:00 Online Learning in Unknown Markov Games
Yi Tian, Yuanhao Wang, Tiancheng Yu, Suvrit Sra
Poster
Wed 21:00 Near-Optimal Model-Free Reinforcement Learning in Non-Stationary Episodic MDPs
Weichao Mao, Kaiqing Zhang, Ruihao Zhu, David Simchi-Levi, Tamer Basar
Poster
Wed 21:00 Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality
Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin LIANG
Poster
Wed 21:00 Improved Corruption Robust Algorithms for Episodic Reinforcement Learning
Yifang Chen, Simon Du, Kevin Jamieson
Poster
Wed 21:00 Incentivized Bandit Learning with Self-Reinforcing User Preferences
Tianchen Zhou, Jia Liu, Chaosheng Dong, jingyuan deng
Poster
Wed 21:00 Beyond $log^2(T)$ regret for decentralized bandits in matching markets
Soumya Basu, Karthik Abinav Sankararaman, Abishek Sankararaman
Poster
Wed 21:00 Robust Policy Gradient against Strong Data Corruption
Xuezhou Zhang, Yiding Chen, Jerry Zhu, Wen Sun
Poster
Wed 21:00 Adapting to misspecification in contextual bandits with offline regression oracles
Sanath Kumar Krishnamurthy, Vitor Hadad, Susan Athey
Poster
Wed 21:00 Massively Parallel and Asynchronous Tsetlin Machine Architecture Supporting Almost Constant-Time Scaling
Kuruge Darshana Abeyrathna, Bimal Bhattarai, Morten Goodwin, Saeed Rahimi Gorji, Ole-Christoffer Granmo, Lei Jiao, Rupsa Saha, Rohan Kumar Yadav
Poster
Wed 21:00 Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning
Xutong Liu, Jinhang Zuo, Xiaowei Chen, Wei Chen, John C. S. Lui
Poster
Wed 21:00 Randomized Exploration in Reinforcement Learning with General Value Function Approximation
Haque Ishfaq, Qiwen Cui, Viet Nguyen, Alex Ayoub, Zhuoran Yang, Zhaoran Wang, Doina Precup, Lin Yang
Poster
Wed 21:00 Combinatorial Blocking Bandits with Stochastic Delays
Alexia Atsidakou, Orestis Papadigenopoulos, Soumya Basu, Constantine Caramanis, Sanjay Shakkottai
Poster
Wed 21:00 Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously
Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang, Xiaojin Zhang
Poster
Wed 21:00 Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping
Dongruo Zhou, Jiafan He, Quanquan Gu
Poster
Wed 21:00 Dynamic Balancing for Model Selection in Bandits and RL
Ashok Cutkosky, Christoph Dann, Abhimanyu Das, Claudio Gentile, Aldo Pacchiano, Manish Purohit
Poster
Wed 21:00 Confidence-Budget Matching for Sequential Budgeted Learning
Yonathan Efroni, Nadav Merlis, Aadirupa Saha, Shie Mannor
Poster
Wed 21:00 AdaXpert: Adapting Neural Architecture for Growing Data
Shuaicheng Niu, Jiaxiang Wu, Guanghui Xu, Yifan Zhang, Yong Guo, Peilin Zhao, Peng Wang, Mingkui Tan
Poster
Wed 21:00 Top-k eXtreme Contextual Bandits with Arm Hierarchy
Rajat Sen, Alexander Rakhlin, Lexing Ying, Rahul Kidambi, Dean Foster, Daniel Hill, Inderjit Dhillon
Poster
Wed 21:00 Logarithmic Regret for Reinforcement Learning with Linear Function Approximation
Jiafan He, Dongruo Zhou, Quanquan Gu
Poster
Wed 21:00 CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee
Tengyu Xu, Yingbin LIANG, Guanghui Lan
Poster
Wed 21:00 Robust Pure Exploration in Linear Bandits with Limited Budget
Ayya Alieva, Ashok Cutkosky, Abhimanyu Das
Poster
Wed 21:00 A Sharp Analysis of Model-based Reinforcement Learning with Self-Play
Qinghua Liu, Tiancheng Yu, Yu Bai, Chi Jin
Poster
Wed 21:00 Interaction-Grounded Learning
Tengyang Xie, John Langford, Paul Mineiro, Ida Momennejad
Poster
Wed 21:00 Task-Optimal Exploration in Linear Dynamical Systems
Andrew Wagenmaker, Max Simchowitz, Kevin Jamieson
Poster
Wed 21:00 Breaking the Deadly Triad with a Target Network
Shangtong Zhang, Hengshuai Yao, Shimon Whiteson
Poster
Wed 21:00 SAINT-ACC: Safety-Aware Intelligent Adaptive Cruise Control for Autonomous Vehicles Using Deep Reinforcement Learning
Lokesh Chandra Das, Myounggyu Won
Poster
Wed 21:00 Sparsity-Agnostic Lasso Bandit
Min-hwan Oh, Garud Iyengar, Assaf Zeevi
Poster
Wed 21:00 Quantile Bandits for Best Arms Identification
Mengyan Zhang, Cheng Soon Ong
Poster
Wed 21:00 Pure Exploration and Regret Minimization in Matching Bandits
Flore Sentenac, Jialin Yi, Clément Calauzènes, Vianney Perchet, Milan Vojnovic
Poster
Wed 21:00 Provably Efficient Algorithms for Multi-Objective Competitive RL
Tiancheng Yu, Yi Tian, Jingzhao Zhang, Suvrit Sra
Poster
Wed 21:00 Resource Allocation in Multi-armed Bandit Exploration: Overcoming Sublinear Scaling with Adaptive Parallelism
Brijen Thananjeyan, Kirthevasan Kandasamy, Ion Stoica, Michael Jordan, Ken Goldberg, Joseph E Gonzalez
Poster
Wed 21:00 Improved Regret Bounds of Bilinear Bandits using Action Space Analysis
Kyoungseok Jang, Kwang-Sung Jun, Se-Young Yun, Wanmo Kang
Poster
Wed 21:00 A Differentiable Point Process with Its Application to Spiking Neural Networks
Hiroshi Kajino
Poster
Wed 21:00 Optimal Streaming Algorithms for Multi-Armed Bandits
Tianyuan Jin, Keke Huang, Jing Tang, Xiaokui Xiao
Poster
Wed 21:00 Almost Optimal Anytime Algorithm for Batched Multi-Armed Bandits
Tianyuan Jin, Jing Tang, Pan Xu, Keke Huang, Xiaokui Xiao, Quanquan Gu
Poster
Wed 21:00 Cyclically Equivariant Neural Decoders for Cyclic Codes
Xiangyu Chen, Min Ye
Poster
Wed 21:00 Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient
Botao Hao, Yaqi Duan, Tor Lattimore, Csaba Szepesvari, Mengdi Wang
Poster
Wed 21:00 Dynamic Planning and Learning under Recovering Rewards
David Simchi-Levi, Zeyu Zheng, Feng Zhu
Poster
Wed 21:00 Fast active learning for pure exploration in reinforcement learning
Pierre MENARD, Omar Darwiche Domingues, Anders Jonsson, Emilie Kaufmann, Edouard Leurent, Michal Valko
Poster
Wed 21:00 Provably Correct Optimization and Exploration with Non-linear Policies
Fei Feng, Wotao Yin, Alekh Agarwal, Lin Yang
Poster
Wed 21:00 Approximation Theory Based Methods for RKHS Bandits
Sho Takemori, Masahiro Sato
Poster
Wed 21:00 UCB Momentum Q-learning: Correcting the bias without forgetting
Pierre MENARD, Omar Darwiche Domingues, Xuedong Shang, Michal Valko
Poster
Wed 21:00 Deep Coherent Exploration for Continuous Control
Yijie Zhang, Herke van Hoof
Poster
Wed 21:00 Sample Efficient Reinforcement Learning In Continuous State Spaces: A Perspective Beyond Linearity
Dhruv Malik, Aldo Pacchiano, Vishwak Srinivasan, Yuanzhi Li
Poster
Wed 21:00 The Symmetry between Arms and Knapsacks: A Primal-Dual Approach for Bandits with Knapsacks
Xiaocheng Li, Chunlin Sun, Yinyu Ye
Oral
Thu 5:00 Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment
Michael Chang, Sid Kaushik, Sergey Levine, Thomas Griffiths
Oral Session
Thu 5:00 Reinforcement Learning 15
Spotlight
Thu 5:45 Parallel Droplet Control in MEDA Biochips using Multi-Agent Reinforcement Learning
Tung-Che Liang, Jin Zhou, Yun-Sheng Chan, Tsung-Yi Ho, Krishnendu Chakrabarty, Cy Lee
Spotlight
Thu 5:45 Detecting Rewards Deterioration in Episodic Reinforcement Learning
Ido Greenberg, Shie Mannor
Oral
Thu 6:00 Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
Adam Foster, Desi Ivanova, ILYAS MALIK, Tom Rainforth
Spotlight
Thu 6:25 Off-Policy Confidence Sequences
Nikos Karampatziakis, Paul Mineiro, Aaditya Ramdas
Spotlight
Thu 6:35 Quantum algorithms for reinforcement learning with a generative model
Daochen Wang, Aarthi Sundaram, Robin Kothari, Ashish Kapoor, Martin Roetteler
Spotlight
Thu 6:40 Posterior Value Functions: Hindsight Baselines for Policy Gradient Methods
Chris Nota, Philip Thomas, Bruno C. da Silva
Spotlight
Thu 6:40 Decoupling Representation Learning from Reinforcement Learning
Adam Stooke, Kimin Lee, Pieter Abbeel, Michael Laskin
Oral
Thu 7:00 Modeling Hierarchical Structures with Continuous Recursive Neural Networks
Jishnu Ray Chowdhury, Cornelia Caragea
Spotlight
Thu 7:20 Unified Robust Semi-Supervised Variational Autoencoder
Xu Chen
Spotlight
Thu 7:35 Online Limited Memory Neural-Linear Bandits with Likelihood Matching
Ofir Nabati, Tom Zahavy, Shie Mannor
Poster
Thu 9:00 Posterior Value Functions: Hindsight Baselines for Policy Gradient Methods
Chris Nota, Philip Thomas, Bruno C. da Silva
Poster
Thu 9:00 Parallel Droplet Control in MEDA Biochips using Multi-Agent Reinforcement Learning
Tung-Che Liang, Jin Zhou, Yun-Sheng Chan, Tsung-Yi Ho, Krishnendu Chakrabarty, Cy Lee
Poster
Thu 9:00 Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
Adam Foster, Desi Ivanova, ILYAS MALIK, Tom Rainforth
Poster
Thu 9:00 Online Limited Memory Neural-Linear Bandits with Likelihood Matching
Ofir Nabati, Tom Zahavy, Shie Mannor
Poster
Thu 9:00 Adapting to Delays and Data in Adversarial Multi-Armed Bandits
András György, Pooria Joulani
Poster
Thu 9:00 Unified Robust Semi-Supervised Variational Autoencoder
Xu Chen
Poster
Thu 9:00 Modeling Hierarchical Structures with Continuous Recursive Neural Networks
Jishnu Ray Chowdhury, Cornelia Caragea
Poster
Thu 9:00 Detecting Rewards Deterioration in Episodic Reinforcement Learning
Ido Greenberg, Shie Mannor
Poster
Thu 9:00 Quantum algorithms for reinforcement learning with a generative model
Daochen Wang, Aarthi Sundaram, Robin Kothari, Ashish Kapoor, Martin Roetteler
Poster
Thu 9:00 Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment
Michael Chang, Sid Kaushik, Sergey Levine, Thomas Griffiths
Poster
Thu 9:00 Decoupling Representation Learning from Reinforcement Learning
Adam Stooke, Kimin Lee, Pieter Abbeel, Michael Laskin
Poster
Thu 9:00 Off-Policy Confidence Sequences
Nikos Karampatziakis, Paul Mineiro, Aaditya Ramdas
Thu 17:00 RL Social
Dibya Ghosh, Hager Radi, Derek Li, Alex Ayoub, Erfan Miahi, Rishabh Agarwal, Charline Le Lan, Abhishek Naik, John Martin, Shruti Mishra, Adrien Ali Taiga
Spotlight
Thu 17:25 REPAINT: Knowledge Transfer in Deep Reinforcement Learning
Yunzhe Tao, Sahika Genc, Jonathan Chung, TAO SUN, Sunil Mallya
Spotlight
Thu 17:40 Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning
Luisa Zintgraf, Leo Feng, Cong Lu, Max Igl, Kristian Hartikainen, Katja Hofmann, Shimon Whiteson
Spotlight
Thu 17:45 Structured World Belief for Reinforcement Learning in POMDP
Gautam Singh, Skand Peri, Junghyun Kim, Hyunseok Kim, Sungjin Ahn
Spotlight
Thu 18:25 Breaking the Deadly Triad with a Target Network
Shangtong Zhang, Hengshuai Yao, Shimon Whiteson
Spotlight
Thu 18:25 Policy Caches with Successor Features
Mark Nemecek, Ron Parr
Spotlight
Thu 18:30 MetaCURE: Meta Reinforcement Learning with Empowerment-Driven Exploration
Jin Zhang, Jianhao Wang, Hao Hu, Tong Chen, Yingfeng Chen, Changjie Fan, Chongjie Zhang
Spotlight
Thu 18:30 Meta-Thompson Sampling
Branislav Kveton, Mikhail Konobeev, Manzil Zaheer, Chih-wei Hsu, Martin Mladenov, Craig Boutilier, Csaba Szepesvari
Spotlight
Thu 18:35 Offline Meta-Reinforcement Learning with Advantage Weighting
Eric Mitchell, Rafael Rafailov, Xue Bin Peng, Sergey Levine, Chelsea Finn
Spotlight
Thu 18:35 Decentralized Single-Timescale Actor-Critic on Zero-Sum Two-Player Stochastic Games
Hongyi Guo, Zuyue Fu, Zhuoran Yang, Zhaoran Wang
Spotlight
Thu 18:45 Temporal Predictive Coding For Model-Based Planning In Latent Space
Tung Nguyen, Rui Shu, Tuan Pham, Hung Bui, Stefano Ermon
Spotlight
Thu 19:20 Near-Optimal Entrywise Anomaly Detection for Low-Rank Matrices with Sub-Exponential Noise
Vivek Farias, Andrew Li, Tianyi Peng
Spotlight
Thu 20:30 On Lower Bounds for Standard and Robust Gaussian Process Bandit Optimization
Xu Cai, Jonathan Scarlett
Spotlight
Thu 20:35 Boosting for Online Convex Optimization
Elad Hazan, Karan Singh
Spotlight
Thu 20:35 Optimal Thompson Sampling strategies for support-aware CVaR bandits
Dorian Baudry, Romain Gautron, Emilie Kaufmann, Odalric-Ambrym Maillard
Spotlight
Thu 20:40 On Limited-Memory Subsampling Strategies for Bandits
Dorian Baudry, Yoan Russac, Olivier Cappé
Spotlight
Thu 20:45 Problem Dependent View on Structured Thresholding Bandit Problems
James Cheshire, Pierre MENARD, Alexandra Carpentier
Spotlight
Thu 20:45 CURI: A Benchmark for Productive Concept Learning Under Uncertainty
Rama Vedantam, Arthur Szlam, Max Nickel, Ari Morcos, Brenden Lake
Spotlight
Thu 20:50 Leveraging Good Representations in Linear Contextual Bandits
Matteo Papini, Andrea Tirinzoni, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta
Poster
Thu 21:00 Structured World Belief for Reinforcement Learning in POMDP
Gautam Singh, Skand Peri, Junghyun Kim, Hyunseok Kim, Sungjin Ahn
Poster
Thu 21:00 Near-Optimal Entrywise Anomaly Detection for Low-Rank Matrices with Sub-Exponential Noise
Vivek Farias, Andrew Li, Tianyi Peng
Poster
Thu 21:00 Offline Meta-Reinforcement Learning with Advantage Weighting
Eric Mitchell, Rafael Rafailov, Xue Bin Peng, Sergey Levine, Chelsea Finn
Poster
Thu 21:00 Meta-Thompson Sampling
Branislav Kveton, Mikhail Konobeev, Manzil Zaheer, Chih-wei Hsu, Martin Mladenov, Craig Boutilier, Csaba Szepesvari
Poster
Thu 21:00 REPAINT: Knowledge Transfer in Deep Reinforcement Learning
Yunzhe Tao, Sahika Genc, Jonathan Chung, TAO SUN, Sunil Mallya
Poster
Thu 21:00 Leveraging Good Representations in Linear Contextual Bandits
Matteo Papini, Andrea Tirinzoni, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta
Poster
Thu 21:00 Optimal Thompson Sampling strategies for support-aware CVaR bandits
Dorian Baudry, Romain Gautron, Emilie Kaufmann, Odalric-Ambrym Maillard
Poster
Thu 21:00 On Limited-Memory Subsampling Strategies for Bandits
Dorian Baudry, Yoan Russac, Olivier Cappé
Poster
Thu 21:00 On Lower Bounds for Standard and Robust Gaussian Process Bandit Optimization
Xu Cai, Jonathan Scarlett
Poster
Thu 21:00 Policy Caches with Successor Features
Mark Nemecek, Ron Parr
Poster
Thu 21:00 Temporal Predictive Coding For Model-Based Planning In Latent Space
Tung Nguyen, Rui Shu, Tuan Pham, Hung Bui, Stefano Ermon
Poster
Thu 21:00 Boosting for Online Convex Optimization
Elad Hazan, Karan Singh
Poster
Thu 21:00 Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning
Luisa Zintgraf, Leo Feng, Cong Lu, Max Igl, Kristian Hartikainen, Katja Hofmann, Shimon Whiteson
Poster
Thu 21:00 Problem Dependent View on Structured Thresholding Bandit Problems
James Cheshire, Pierre MENARD, Alexandra Carpentier
Poster
Thu 21:00 MetaCURE: Meta Reinforcement Learning with Empowerment-Driven Exploration
Jin Zhang, Jianhao Wang, Hao Hu, Tong Chen, Yingfeng Chen, Changjie Fan, Chongjie Zhang
Poster
Thu 21:00 CURI: A Benchmark for Productive Concept Learning Under Uncertainty
Rama Vedantam, Arthur Szlam, Max Nickel, Ari Morcos, Brenden Lake
Poster
Thu 21:00 Decentralized Single-Timescale Actor-Critic on Zero-Sum Two-Player Stochastic Games
Hongyi Guo, Zuyue Fu, Zhuoran Yang, Zhaoran Wang
Workshop
Fri 2:00 Challenges in Deploying and monitoring Machine Learning Systems
Alessandra Tosi, Nathan Korda, Michael A Osborne, Stephen Roberts, Andrei Paleyes, Fariba Yousefi
Workshop
Fri 5:45 ICML 2021 Workshop on Unsupervised Reinforcement Learning
Feryal Behbahani, Joelle Pineau, Lerrel Pinto, Roberta Raileanu, Aravind Srinivas, Denis Yarats, Amy Zhang
Workshop
Fri 6:00 Reinforcement Learning for Real Life
Yuxi Li, Minmin Chen, Omer Gottesman, Lihong Li, Zongqing Lu, Rupam Mahmood, Niranjani Prasad, Zhiwei (Tony) Qin, Csaba Szepesvari, Matthew Taylor
Workshop
Fri 7:37 Meta Learning the Step Size in Policy Gradient Methods
Luca Sabbioni
Workshop
Fri 8:00 Poster session 1
Workshop
Fri 9:15 Reinforcement Learning for Optimal Frequency Control: A Lyapunov Approach
Wenqi Cui
Workshop
Fri 12:25 Paper Presentation 2: Leveraging Reinforcement Learning to build a Recommendation System for Incognito mode Users
Kishor Datta Gupta, Nafiz Sadman
Workshop
Sat 9:00 Workshop on Reinforcement Learning Theory
Shipra Agrawal, Simon Du, Niao He, Csaba Szepesvari, Lin Yang
Workshop
Sat 10:15 On the Theory of Reinforcement Learning with Once-per-Episode Feedback
Niladri Chatterji, Aldo Pacchiano, Peter Bartlett, Michael Jordan
Workshop
Sat 10:45 Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning
Andrea Zanette, Martin Wainwright, Emma Brunskill
Workshop
Sat 11:00 Invited Speaker: Animashree Anandkumar: Stability-aware reinforcement learning in dynamical systems
Animashree Anandkumar
Workshop
Sat 14:00 Invited Speaker: Bo Dai: Leveraging Non-uniformity in Policy Gradient
Bo Dai
Workshop
Sat 14:30 Invited Speaker: Qiaomin Xie: Reinforcement Learning for Zero-Sum Markov Games Using Function Approximation and Correlated Equilibrium
Qiaomin Xie
Workshop
Sat 15:00 Bad-Policy Density: A Measure of Reinforcement-Learning Hardness
Dave Abel, Cameron Allen, Dilip Arumugam, D Ellis Hershkowitz, Michael L. Littman, Lawson Wong
Workshop
Sat 15:15 Sample-Efficient Learning of Stackelberg Equilibria in General-Sum Games
Yu Bai, Chi Jin, Huan Wang, Caiming Xiong
Workshop
Sat 15:45 CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee
Tengyu Xu, Yingbin LIANG, Guanghui Lan
Workshop
Sat 16:00 Invited Speaker: Art Owen: Empirical likelihood for reinforcement learning
Workshop
Sat 17:45 Value-Based Deep Reinforcement Learning Requires Explicit Regularization
Aviral Kumar, Rishabh Agarwal, Aaron Courville, Tengyu Ma, George Tucker, Sergey Levine
Workshop
Safe Deep Reinforcement Learning for Multi-Agent Systems with Continuous Action Spaces
Athina Nisioti, Dario Pavllo, Jonas Kohler
Workshop
Reinforcement Learning with Logical Action-Aware Features for Polymer Discovery
Sarath Swaminathan, Dmitry Zubarev, Subhajit Chaudhury, Asim Munawar
Workshop
Constraints Penalized Q-Learning for Safe Offline Reinforcement Learning
Haoran Xu, Xianyuan Zhan, Xiangyu Zhu
Workshop
ModelLight: Model-Based Meta-Reinforcement Learning for Traffic Signal Control
Xingshuai Huang, di wu, Benoit Boulet
Workshop
Robust Risk-Sensitive Reinforcement Learning Agents for Trading Markets
Yue Gao, Pablo Hernandez-Leal, Kry Yik Chau Lui
Workshop
Automating Power Networks: Improving RL Agent Robustness with Adversarial Training
Alex Pan, Yongkyun Lee, Huan Zhang
Workshop
Understanding the Generalization Gap in Visual Reinforcement Learning
aajay3110 Ajay, Ge Yang, Ofir Nachum, Pulkit Agrawal
Workshop
Reset-Free Reinforcement Learning via Multi-Task Learning: Learning Dexterous Manipulation Behaviors without Human Intervention
Abhishek Gupta, Justin Yu, Tony Z. Zhao, Vikash Kumar, Aaron Rovinsky, Kelvin Xu, Thomas Devlin, Sergey Levine
Workshop
Attend2Pack: Bin Packing through Deep Reinforcement Learning with Attention
Jingwei Zhang, Bin Zi, Xiaoyu Ge
Workshop
Designing Interpretable Approximations to Deep Reinforcement Learning
Nathan Dahlin, Rahul Jain, Pierluigi Nuzzo, Krishna Kalagarla, Nikhil Naik
Workshop
Decision Transformer: Reinforcement Learning via Sequence Modeling
Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch
Workshop
Multi-Task Offline Reinforcement Learning with Conservative Data Sharing
Tianhe (Kevin) Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Sergey Levine, Chelsea Finn
Workshop
Value-Based Deep Reinforcement Learning Requires Explicit Regularization
Aviral Kumar, Rishabh Agarwal, Aaron Courville, Tengyu Ma, George Tucker, Sergey Levine
Workshop
A Policy Efficient Reduction Approach to Convex Constrained Deep Reinforcement Learning
Tianchi Cai, Wenpeng Zhang, Lihong Gu, Xiaodong Zeng, Jinjie Gu
Workshop
Reinforcement Learning Agent Training with Goals for Real World Tasks
Xuan Zhao
Workshop
RRL: Resnet as representation for Reinforcement Learning
Rutav Shah, Vikash Kumar
Workshop
Value-Based Deep Reinforcement Learning Requires Explicit Regularization
Aviral Kumar, Rishabh Agarwal, Aaron Courville, Tengyu Ma, George Tucker, Sergey Levine
Workshop
Bad-Policy Density: A Measure of Reinforcement-Learning Hardness
Dave Abel, Cameron Allen, Dilip Arumugam, D Ellis Hershkowitz, Michael L. Littman, Lawson Wong
Workshop
CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee
Tengyu Xu, Yingbin LIANG, Guanghui Lan
Workshop
Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning
Andrea Zanette, Martin Wainwright, Emma Brunskill
Workshop
On the Theory of Reinforcement Learning with Once-per-Episode Feedback
Niladri Chatterji, Aldo Pacchiano, Peter Bartlett, Michael Jordan
Workshop
Sample-Efficient Learning of Stackelberg Equilibria in General-Sum Games
Yu Bai, Chi Jin, Huan Wang, Caiming Xiong
Workshop
Improving Human Decision-Making with Machine Learning
Hamsa Bastani, Osbert Bastani, Park Sinchaisri
Workshop
Convergence of a Human-in-the-Loop Policy-Gradient Algorithm With Eligibility Trace Under Reward, Policy, and Advantage Feedback
Ishaan Shah, David Halpern, Michael L. Littman, Kavosh Asadi
Workshop
Explaining Reinforcement Learning Policies through Counterfactual Trajectories
Julius Frost, Olivia Watkins, Eric Weiner, Pieter Abbeel, Prof. Darrell, Bryan Plummer, Kate Saenko
Workshop
Explicable Policy Search via Preference-Based Learning under Human Biases
Ze Gong, Yu Zhang
Workshop
Accelerating the Convergence of Human-in-the-Loop Reinforcement Learning with Counterfactual Explanations
Jakob Karalus, Felix Lindner
Workshop
Offline Reinforcement Learning as Anti-Exploration
Shideh Rezaeifar, Robert Dadashi, Nino Vieillard, Léonard Hussenot, Olivier Bachem, Olivier Pietquin, Matthieu Geist
Workshop
A Set-Theoretic Approach to Safe Reinforcement Learning in Power Systems
Daniel Tabas
Workshop
A Reinforcement Learning Approach to Home Energy Management for Modulating Heat Pumps and Photovoltaic Systems
Lissy Langer
Workshop
Preserving the integrity of the Canadian northern ecosystems through insights provided by reinforcement learning-based Arctic fox movement models
Catherine Villeneuve
Workshop
Power Grid Cascading Failure Mitigation by Reinforcement Learning
Yongli Zhu
Workshop
Active Automaton Inference for Reinforcement Learning using Queries and Counterexamples
icml2021xai, Adi Ojha, Zhe Xu, Ufuk Topcu
Workshop
Adversarially Trained Neural Policies in the Fourier Domain
Ezgi Korkmaz
Workshop
Non-Robust Feature Mapping in Deep Reinforcement Learning
Ezgi Korkmaz
Workshop
Towards Safe Reinforcement Learning via Constraining Conditional Value at Risk
Chengyang Ying, Lemon Zhou, Dong Yan, Jun Zhu
Workshop
Strategically-timed State-Observation Attacks on Deep Reinforcement Learning Agents
You Qiaoben, Lemon Zhou, Chengyang Ying, Jun Zhu
Workshop
Using Logical Specifications of Objectives in Multi-Objective Reinforcement Learning
Kolby Nottingham
Workshop
Poster: Reinforcement Learning for Optimal Frequency Control: A Lyapunov Approach
Workshop
Implicit Ensemble Training for Efficient and Robust Multiagent Reinforcement Learning
Workshop
Safety & Exploration: A Comparative Study of Uses of Uncertainty in Reinforcement Learning
Workshop
Objective Robustness in Deep Reinforcement Learning
Workshop
Relational Deep Reinforcement Learning and Latent Goals for Following Instructions in Temporal Logic
Workshop
AutoMixup: Learning mix-up policies with Reinforcement Learning
Long Luu, Zeyi Huang, Haohan Wang
Workshop
Active privacy-utility trade-off against a hypothesis testing adversary
Ecenaz Erdemir, Pier Luigi Dragotti, Deniz Gunduz
Workshop
Meta Learning the Step Size in Policy Gradient Methods
Luca Sabbioni, Francesco Corda, Marcello Restelli
Workshop
MACDA: Counterfactual Explanation with Multi-Agent Reinforcement Learning for Drug Target Prediction
Tri Nguyen, Thomas Quinn, Thin Nguyen, Truyen Tran
Workshop
Reinforcement Learning for Workflow Recognition in Surgical Videos
Wang Wei, Jingze Zhang, Qi Dou
Workshop
Learning sparse symbolic policies for sepsis treatment
Jacob Pettit, Brenden Petersen, Leno Silva, Gary An, Daniel Faissol
Workshop
Enabling risk-aware Reinforcement Learning for medical interventions through uncertainty decomposition
Paul Festor, Giulia Luise, Matthieu Komorowski, Aldo Faisal
Workshop
Finding the Near Optimal Policy via Reductive Regularization in MDPs
Wenhao Yang, Xiang Li, Guangzeng Xie, Zhihua Zhang
Workshop
Finite Sample Analysis of Average-Reward TD Learning and $Q$-Learning
Sheng Zhang, Zhe Zhang, Siva Maguluri
Workshop
Sample Complexity of Offline Reinforcement Learning with Deep ReLU Networks
Thanh Nguyen-Tang, Sunil Gupta, Hung Tran-The, Svetha Venkatesh
Workshop
Triple-Q: A Model-Free Algorithm for Constrained Reinforcement Learning with Sublinear Regret and Zero Constraint Violation
Honghao Wei, Xin Liu, Lei Ying
Workshop
Marginalized Operators for Off-Policy Reinforcement Learning
Yunhao Tang, Mark Rowland, Remi Munos, Michal Valko
Workshop
On Overconservatism in Offline Reinforcement Learning
Karush Suri, Florian Shkurti
Workshop
Nonstationary Reinforcement Learning with Linear Function Approximation
Huozhi Zhou, Jinglin Chen, Lav Varshney, Ashish Jagmohan
Workshop
Derivative-Free Policy Optimization for Linear Risk-Sensitive and Robust Control Design: Implicit Regularization and Sample Complexity
Kaiqing Zhang, Xiangyuan Zhang, Bin Hu, Tamer Basar
Workshop
When Is Generalizable Reinforcement Learning Tractable?
Dhruv Malik, Yuanzhi Li, Pradeep Ravikumar
Workshop
Efficient Inverse Reinforcement Learning of Transferable Rewards
Giorgia Ramponi, Alberto Maria Metelli, Marcello Restelli
Workshop
Learning to Observe with Reinforcement Learning
Mehmet Koseoglu, Ece Kunduracioglu, Ayca Ozcelikkale
Workshop
Sample Efficient Reinforcement Learning In Continuous State Spaces: A Perspective Beyond Linearity
Dhruv Malik, Aldo Pacchiano, Vishwak Srinivasan, Yuanzhi Li
Workshop
Bagged Critic for Continuous Control
Payal Bawa
Workshop
Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection
Matteo Papini, Andrea Tirinzoni, Aldo Pacchiano, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta
Workshop
Optimal and instance-dependent oracle inequalities for policy evaluation
Wenlong Mou, Ashwin Pananjady, Martin Wainwright
Workshop
Optimistic Exploration with Backward Bootstrapped Bonus for Deep Reinforcement Learning
Chenjia Bai, Lingxiao Wang, Lei Han, Jianye Hao, Animesh Garg, Peng Liu, Zhaoran Wang
Workshop
Reward-Weighted Regression Converges to a Global Optimum
Francesco Faccio, Rupesh Kumar Srivastava, Jürgen Schmidhuber
Workshop
Comparison and Unification of Three Regularization Methods in Batch Reinforcement Learning
Sarah Rathnam
Workshop
Learning Adversarial Markov Decision Processes with Delayed Feedback
Tal Lancewicki, Aviv Rosenberg, Yishay Mansour
Workshop
Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability
Dibya Ghosh, Jad Rahme, Aviral Kumar, Amy Zhang, Ryan P. Adams, Sergey Levine
Workshop
Randomized Least Squares Policy Optimization
Haque Ishfaq, Zhuoran Yang, Andrei Lupu, Viet Nguyen, Lewis Liu, Riashat Islam, Zhaoran Wang, Doina Precup
Workshop
Gap-Dependent Unsupervised Exploration for Reinforcement Learning
Jingfeng Wu, Vladimir Braverman, Lin Yang
Workshop
Online Learning for Stochastic Shortest Path Model via Posterior Sampling
Mehdi Jafarnia, Liyu Chen, Rahul Jain, Haipeng Luo
Workshop
Provable Model-based Nonlinear Bandit and Reinforcement Learning: Shelve Optimism, Embrace Virtual Curvature
Kefan Dong, Jiaqi Yang, Tengyu Ma
Workshop
Linear Convergence of Entropy-Regularized Natural Policy Gradient with Linear Function Approximation
Semih Cayci, Niao He, R Srikant
Workshop
Decentralized Q-Learning in Zero-sum Markov Games
Kaiqing Zhang, David Leslie, Tamer Basar, Asuman Ozdaglar
Workshop
Model-based Offline Reinforcement Learning with Local Misspecification
Kefan Dong, Ramtin Keramati, Emma Brunskill
Workshop
Nearly Minimax Optimal Regret for Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation
Yue Wu, Dongruo Zhou, Quanquan Gu
Workshop
Learning from an Exploring Demonstrator: Optimal Reward Estimation for Bandits
Wenshuo Guo, Kumar Agrawal, Aditya Grover, Vidya Muthukumar, Ashwin Pananjady
Workshop
Model-Free Approach to Evaluate Reinforcement Learning Algorithms
Denis Belomestny, Ilya Levin, Eric Moulines, Alexey Naumov, Sergey Samsonov, Veronika Zorina
Workshop
Provable RL with Exogenous Distractors via Multistep Inverse Dynamics
Yonathan Efroni, Dipendra Misra, Akshay Krishnamurthy, Alekh Agarwal, John Langford
Workshop
Learning Pareto-Optimal Policies in Low-Rank Cooperative Markov Games
Abhimanyu Dubey, Alex `Sandy' Pentland
Workshop
Optimal Uniform OPE and Model-based Offline Reinforcement Learning in Time-Homogeneous, Reward-Free and Task-Agnostic Settings
Ming Yin, Yu-Xiang Wang
Workshop
Near-Optimal Offline Reinforcement Learning via Double Variance Reduction
Ming Yin, Yu Bai, Yu-Xiang Wang
Workshop
Mixture of Step Returns in Bootstrapped DQN
PoHan Chiang, Hsuan-Kung Yang, Zhang-Wei Hong, Chun-Yi Lee
Workshop
Nearly Optimal Regret for Learning Adversarial MDPs with Linear Function Approximation
Jiafan He, Dongruo Zhou, Quanquan Gu
Workshop
Provably efficient exploration-free transfer RL for near-deterministic latent dynamics
Yao Liu, Dipendra Misra, Miro Dudik, Robert Schapire
Workshop
Mind the Gap: Safely Bridging Offline and Online Reinforcement Learning
Wanqiao Xu, Kan Xu, Hamsa Bastani, Osbert Bastani
Workshop
Invariant Policy Learning: A Causal Perspective
Sorawit Saengkyongam, Nikolaj Thams, Jonas Peters, Niklas Pfister
Workshop
Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning
Tengyang Xie, Nan Jiang, Huan Wang, Caiming Xiong, Yu Bai
Workshop
Online Sub-Sampling for Reinforcement Learning with General Function Approximation
Dingwen Kong, Russ Salakhutdinov, Ruosong Wang, Lin Yang
Workshop
Is Pessimism Provably Efficient for Offline RL?
Ying Jin, Zhuoran Yang, Zhaoran Wang
Workshop
Nearly Minimax Optimal Reinforcement Learning for Discounted MDPs
Jiafan He, Dongruo Zhou, Quanquan Gu
Workshop
A general sample complexity analysis of vanilla policy gradient
Rui Yuan, Robert Gower, Alessandro Lazaric
Workshop
The Power of Exploiter: Provable Multi-Agent RL in Large State Spaces
Chi Jin, Qinghua Liu, Tiancheng Yu
Workshop
Bellman Eluder Dimension: New Rich Classes of RL Problems, and Sample-Efficient Algorithms
Chi Jin, Qinghua Liu, Sobhan Miryoosefi
Workshop
A Short Note on the Relationship of Information Gain and Eluder Dimension
Kaixuan Huang, Sham Kakade, Jason Lee, Qi Lei
Workshop
Convergence and Optimality of Policy Gradient Methods in Weakly Smooth Settings
Matthew Zhang, Murat Erdogdu, Animesh Garg
Workshop
Almost Optimal Algorithms for Two-player Markov Games with Linear Function Approximation
Zixiang Chen, Dongruo Zhou, Quanquan Gu
Workshop
Improved Estimator Selection for Off-Policy Evaluation
George Tucker
Workshop
A Boosting Approach to Reinforcement Learning
Nataly Brukhim, Elad Hazan, Karan Singh
Workshop
Value-Based Deep Reinforcement Learning Requires Explicit Regularization
Aviral Kumar, Rishabh Agarwal, Aaron Courville, Tengyu Ma, George Tucker, Sergey Levine
Workshop
Policy Optimization in Adversarial MDPs: Improved Exploration via Dilated Bonuses
Haipeng Luo, Chen-Yu Wei, Chung-Wei Lee
Workshop
Multi-Task Offline Reinforcement Learning with Conservative Data Sharing
Tianhe (Kevin) Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Sergey Levine, Chelsea Finn
Workshop
Provably Efficient Multi-Task Reinforcement Learning with Model Transfer
Chicheng Zhang, Zhi Wang
Workshop
Reward-Free Policy Space Compression for Reinforcement Learning
Mirco Mutti, Stefano Del Col, Marcello Restelli
Workshop
Learning to Explore Multiple Environments without Rewards
Mirco Mutti, Mattia Mancassola, Marcello Restelli
Workshop
The Importance of Non-Markovianity in Maximum State Entropy Exploration
Mirco Mutti, Riccardo De Santi, Marcello Restelli
Workshop
Direct then Diffuse: Incremental Unsupervised Skill Discovery for State Covering and Goal Reaching
Pierre-Alexan Kamienny, Jean Tarbouriech, Alessandro Lazaric, Ludovic Denoyer
Workshop
Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation
Evgenii Nikishin, Romina Abachi, Rishabh Agarwal, Pierre-Luc Bacon
Workshop
Beyond Fine-Tuning: Transferring Behavior in Reinforcement Learning
Víctor Campos, Pablo Sprechmann, Steven Hansen, Andre Barreto, Steven Kapturowski, Alex Vitvitskyi, Adrià Puigdomenech Badia, Charles Blundell
Workshop
Pretrained Encoders are All You Need
Mina Khan, Advait Rane, Srivatsa P, Shriram Chenniappa, Rishabh Anand, Sherjil Ozair, Patricia Maes
Workshop
Density-Based Bonuses on Learned Representations for Reward-Free Exploration in Deep Reinforcement Learning
Omar Darwiche Domingues, Corentin Tallec, Remi Munos, Michal Valko
Workshop
Learning Task Agnostic Skills with Data-driven Guidance
Even Klemsdal, Sverre Herland, Abdulmajid Murad
Workshop
Stabilizing Deep Q-Learning with ConvNets and Vision Transformers under Data Augmentation
Nicklas Hansen, Hao Su, Xiaolong Wang
Workshop
Disentangled Predictive Representation for Meta-Reinforcement Learning
Sephora Madjiheurem, Laura Toni
Workshop
Decoupling Exploration and Exploitation in Reinforcement Learning
Lukas Schäfer, Filippos Christianos, Josiah Hanna, Stefano V. Albrecht
Workshop
Tangent Space Least Adaptive Clustering
James Buenfil, Samson Koelle, Marina Meila
Workshop
Representation Learning for Out-of-distribution Generalization in Downstream Tasks
Frederik Träuble, Andrea Dittadi, Manuel Wuthrich, Felix Widmaier, Peter V Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer
Workshop
CoBERL: Contrastive BERT for Reinforcement Learning
Andrea Banino, Adrià Puigdomenech Badia, Jacob C Walker, Tim Scholtes, Jovana Mitrovic, Charles Blundell
Workshop
Visual Adversarial Imitation Learning using Variational Models
Rafael Rafailov, Tianhe (Kevin) Yu, Aravind Rajeswaran, Chelsea Finn
Workshop
Decision Transformer: Reinforcement Learning via Sequence Modeling
Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch
Workshop
Reinforcement Learning as One Big Sequence Modeling Problem
Michael Janner, Qiyang Li, Sergey Levine
Workshop
Exploration-Driven Representation Learning in Reinforcement Learning
Akram Erraqabi, Harry Zhao, Marlos C. Machado, Yoshua Bengio, Sainbayar Sukhbaatar, Ludovic Denoyer, Alessandro Lazaric
Workshop
Data-Efficient Exploration with Self Play for Atari
Michael Laskin, Catherine Cang, Ryan Rudes, Pieter Abbeel
Workshop
Intrinsic Control of Variational Beliefs in Dynamic Partially-Observed Visual Environments
Nicholas Rhinehart, Jenny Wang, Glen Berseth, JD Co-Reyes, Danijar Hafner, Chelsea Finn, Sergey Levine
Workshop
Discovering Diverse Nearly Optimal Policies with Successor Features
Tom Zahavy, Brendan O'Donoghue, Andre Barreto, Sebastian Flennerhag, Vlad Mnih, Satinder Singh
Workshop
Reward is enough for convex MDPs
Tom Zahavy, Brendan O'Donoghue, Guillaume Desjardins, Satinder Singh
Workshop
Unsupervised Skill-Discovery and Skill-Learning in Minecraft
Juan José Nieto, Roger Creus Castanyer, Xavier Giro-i-Nieto
Workshop
Learning Task-Relevant Representations with Selective Contrast for Reinforcement Learning in a Real-World Application
Flemming Brieger, Daniel A Braun, Sascha Lange
Workshop
MASAI: Multi-agent Summative Assessment Improvement for Unsupervised Environment Design
Yiping Wang, Brandon Haworth
Workshop
Explore and Control with Adversarial Surprise
Arnaud Fickinger, Natasha Jaques, Samyak Parajuli, Michael Chang, Nicholas Rhinehart, Glen Berseth, Stuart Russell, Sergey Levine
Workshop
Hierarchical Few-Shot Imitation with Skill Transition Models
kourosh hakhamaneshi, Ruihan Zhao, Albert Zhan, Pieter Abbeel, Michael Laskin
Workshop
Visualizing MuZero Models
joery de Vries, Ken Voskuil, Thomas M Moerland, Aske Plaat
Workshop
Did I do that? Blame as a means to identify controlled effects in reinforcement learning
Oriol Corcoll, Raul Vicente
Workshop
NeuRL: Closed-form Inverse Reinforcement Learning for Neural Decoding
Joschka Boedecker
Workshop
DeepThermal: Combustion Optimization for Thermal Power Generating Units Using Offline Reinforcement Learning
Xianyuan Zhan, Haoran Xu, Yue Zhang, Xiangyu Zhu, Honglei Yin
Workshop
Reinforcement Learning for (Mixed) Integer Programming: Smart Feasibility Pump
Mengxin Wang, Meng Qi, Zuo-Jun Shen
Workshop
Continuous Doubly Constrained Batch Reinforcement Learning
Rasool Fakoor, Jonas Mueller, Kavosh Asadi, Pratik Chaudhari, Alex Smola
Workshop
Contingency-Aware Influence Maximization: A Reinforcement Learning Approach
Haipeng Chen, Wei Qiu, Han-Ching Ou, Bo An, Milind Tambe
Workshop
On the Difficulty of Generalizing Reinforcement Learning Framework for Combinatorial Optimization
Mostafa Pashazadeh, Kui Wu
Workshop
OffWorld Gym: Open-Access Physical Robotics Environment for Real-World Reinforcement Learning Benchmark and Research
Ashish Kumar, Toby Buckley, John Lanier, Qiaozhi Wang, Alicia Kavelaars, Ilya Kuzovkin
Workshop
Learning Barrier Certificates: Towards Safe Reinforcement Learning with Zero Training-time Violations
Yuping Luo, Tengyu Ma
Workshop
Automatic Risk Adaptation in Distributional Reinforcement Learning
Frederik Schubert, Theresa Eimer, Bodo Rosenhahn, Marius Lindauer
Workshop
Disentangled Attention as Intrinsic Regularization for Bimanual Multi-Object Manipulation
Minghao Zhang, Pingcheng Jian, Yi Wu, Harry (Huazhe) Xu, Xiaolong Wang
Workshop
Learning Vision-Guided Quadrupedal Locomotionwith Cross-Modal Transformers
Ruihan Yang, Minghao Zhang, Nicklas Hansen, Harry (Huazhe) Xu, Xiaolong Wang
Workshop
Graph Neural Network Reinforcement Learning for Autonomous Mobility-on-Demand Systems
Daniele Gammelli, Kaidi Yang, James Harrison, Filipe Rodrigues, Francisco Pereira, Marco Pavone
Workshop
Reward-Free Attacks in Multi-Agent Reinforcement Learning
Ted Fujimoto, Timothy Doster, Adam Attarian, Jill Brandenberger, Nathan Hodas
Workshop
Evaluating the progress of Deep Reinforcement Learning in the real world: aligning domain-agnostic and domain-specific research
Juan Jose Garau Luis, Edward Crawley, Bruce Cameron
Workshop
Corruption Robust Offline Reinforcement Learning
Xuezhou Zhang, Yiding Chen, Jerry Zhu, Wen Sun
Workshop
Deep Reinforcement Learning for 3D Furniture Layout in Indoor Graphic Scenes
xinhan di, Pengqian Yu
Workshop
Continual Meta Policy Search for Sequential Multi-Task Learning
Glen Berseth, Zhiwei Zhang
Workshop
Reinforcement Learning as One Big Sequence Modeling Problem
Michael Janner, Qiyang Li, Sergey Levine
Workshop
ReLMM: Practical RL for Learning Mobile Manipulation Skills Using Only Onboard Sensors
Charles Sun, Jedrzej Orbik, Coline Devin, Abhishek Gupta, Glen Berseth, Sergey Levine
Workshop
Representation Learning for Out-of-distribution Generalization in Downstream Tasks
Frederik Träuble, Andrea Dittadi, Manuel Wüthrich, Felix Widmaier, Peter Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer
Workshop
Symbolic Relational Deep Reinforcement Learning based on Graph Neural Networks
Jaromír Janisch, Tomas Pevny, Viliam Lisy
Workshop
Hierarchical Multiple-Instance Data Classification with Costly Features
Jaromír Janisch, Tomas Pevny, Viliam Lisy
Workshop
Efficient Exploration by HyperDQN in Deep Reinforcement Learning
Ziniu Li, Yingru Li, Hao Liang, Tong Zhang
Workshop
Revisiting Design Choices in Offline Model Based Reinforcement Learning
Cong Lu, Philip Ball, Jack Parker-Holder, Michael A Osborne, Stephen Roberts
Workshop
De novo drug design using reinforcement learning with graph-based deep generative models
Sara Romeo Atance, Ola Engkvist, Simon Olsson, Rocío Mercado
Workshop
Designing Online Advertisements via Bandit and Reinforcement Learning
Richard Liu, Yusuke Narita, Kohei Yata
Workshop
Semantic Tracklets: An Object-Centric Representation for Visual Multi-Agent Reinforcement Learning
Iou-Jen Liu, Zhongzheng Ren, Raymond Yeh, Alex Schwing
Workshop
Model Selection for Offline Reinforcement Learning: Practical Considerations for Healthcare Settings
Shengpu Tang, Jenna Wiens
Workshop
IV-RL: Leveraging Target Uncertainty Estimation for Sample Efficiency in Deep Reinforcement Learning
Vincent Mai, Kaustubh Mani, Liam Paull
Workshop
Learning a Markov Model for evaluating Soccer Decision Making
Maaike Van Roy, Pieter Robberechts, Wen-Chi Yang, Luc De Raedt, Jesse Davis
Workshop
AppBuddy: Learning to Accomplish Tasks in Mobile Apps via Reinforcement Learning
Maayan Shvo, Zhiming Hu, Rodrigo A Toro Icarte, Iqbal Mohomed, Allan Jepson, Sheila McIlraith
Workshop
Reward Shaping for User Satisfaction in a REINFORCE Recommender
Konstantina Christakopoulou, Can Xu, Sai Zhang, Sriraj Badam, Daniel Li, Hao Wan, Xinyang Yi, Ya Le, Chris Berg, Eric Bencomo Dixon, Ed Chi, Minmin Chen
Workshop
Learning Action Translator for Meta Reinforcement Learning on Sparse-Reward Tasks
Yijie Guo, Qiucheng Wu, Honglak Lee
Workshop
Mind the Gap: Safely Bridging Offline and Online Reinforcement Learning
Wanqiao Xu, Kan Xu, Hamsa Bastani, Osbert Bastani
Workshop
The Reflective Explorer: Online Meta-Exploration from Offline Data in Visual Tasks with Sparse Rewards
Rafael Rafailov, Varun Kumar, Tianhe (Kevin) Yu, Avi Singh, mariano phielipp, Chelsea Finn
Workshop
Avoiding Overfitting to the Importance Weights in Offline Policy Optimization
Yao Liu, Emma Brunskill
Workshop
Towards Reinforcement Learning for Pivot-based Neural Machine Translation with Non-autoregressive Transformer
Evgeniia Tokarchuk, Jan Rosendahl, Weiyue Wang, Pavel Petrushkov, Tomer Lancewicki, Shahram Khadivi, Hermann Ney
Workshop
Data-Pooling Reinforcement Learning for Personalized Healthcare Intervention
Xinyun Chen, Pengyi Shi
Workshop
Objective Robustness in Deep Reinforcement Learning
Lauro Langosco di Langosco, Lee Sharkey
Workshop
Is Bang-Bang Control All You Need?
Tim Seyde, Igor Gilitschenski, Wilko Schwarting, Bartolomeo Stellato, Martin Riedmiller, Markus Wulfmeier, Daniela Rus