266 Results

Expo Talk Panel
Sun 6:30 Federated Reinforcement Learning for Financial Portfolio Optimization Using the IBM Federated Learning (IFL) Platform
Mary Ellen Perry
Tutorial
Mon 1:00 Machine Learning with Signal Processing
Arno Solin
Tutorial
Mon 5:00 Causal Reinforcement Learning
Elias Bareinboim
AffinityWorkshop
Mon 5:15 Using knowledge from multiple sources to accelerate reinforcement learning
Anna Reali
AffinityWorkshop
Mon 7:30 Keynote speakers: Q&A - 1 + MC
Ivan Dario Arraut Guerrero
AffinityWorkshop
Mon 7:55 Feedback Controller for 3D Dynamic Walking using Reinforcement Learning and Hybrid Zero Dynamics
Guillermo Castillo Martinez
Tutorial
Mon 8:00 Model-Based Methods in Reinforcement Learning
Igor Mordatch, Jessica Hamrick
AffinityWorkshop
Mon 11:00 Invited Talk: Doina Precup on Building Knowledge for AI Agents with Reinforcement Learning
Doina Precup
AffinityWorkshop
Mon 11:35 Breakout Session 4.8: Continual Reinforcement Learning
AffinityWorkshop
Mon 11:35 Breakout Session 4.3: Coping with Sample Inefficiency of Deep-Reinforcement Learning (DRL) for Embodied AI
Poster
Tue 7:00 Loss Function Search for Face Recognition
Xiaobo Wang, Shuo Wang, Cheng Chi, Shifeng Zhang, Tao Mei
Poster
Tue 7:00 Asynchronous Coagent Networks
James Kostas, Chris Nota, Philip Thomas
Poster
Tue 7:00 Improving the Gating Mechanism of Recurrent Neural Networks
Albert Gu, Caglar Gulcehre, Thomas Paine, Matthew Hoffman, Razvan Pascanu
Poster
Tue 7:00 Taylor Expansion Policy Optimization
Yunhao Tang, Michal Valko, Remi Munos
Poster
Tue 7:00 Evaluating the Performance of Reinforcement Learning Algorithms
Scott Jordan, Yash Chandak, Daniel Cohen, Mengxue Zhang, Philip Thomas
Poster
Tue 7:00 On the Global Optimality of Model-Agnostic Meta-Learning
Lingxiao Wang, Qi Cai, Zhuoran Yang, Zhaoran Wang
Poster
Tue 7:00 What is Local Optimality in Nonconvex-Nonconcave Minimax Optimization?
Chi Jin, Praneeth Netrapalli, Michael Jordan
Poster
Tue 7:00 Private Reinforcement Learning with PAC and Regret Guarantees
Giuseppe Vietri, Borja de Balle Pigem, Akshay Krishnamurthy, Steven Wu
Poster
Tue 7:00 Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential Advertising
Xiaotian Hao, Zhaoqing Peng, Yi Ma, Guan Wang, Junqi Jin, Jianye Hao, Shan Chen, Rongquan Bai, Mingzhou Xie, Miao Xu, Zhenzhe Zheng, Chuan Yu, HAN LI, Jian Xu, Kun Gai
Poster
Tue 7:00 Provably Efficient Exploration in Policy Optimization
Qi Cai, Zhuoran Yang, Chi Jin, Zhaoran Wang
Poster
Tue 7:00 From Importance Sampling to Doubly Robust Policy Gradient
Jiawei Huang, Nan Jiang
Poster
Tue 7:00 What Can Learned Intrinsic Rewards Capture?
Zeyu Zheng, Junhyuk Oh, Matteo Hessel, Zhongwen Xu, Manuel Kroiss, Hado van Hasselt, David Silver, Satinder Singh
Poster
Tue 7:00 Q-value Path Decomposition for Deep Multiagent Reinforcement Learning
Yaodong Yang, Jianye Hao, Guangyong Chen, Hongyao Tang, Yingfeng Chen, Yujing Hu, Changjie Fan, Zhongyu Wei
Poster
Tue 7:00 Online Learning for Active Cache Synchronization
Andrey Kolobov, Sebastien Bubeck, Julian Zimmert
Poster
Tue 7:00 Optimizing for the Future in Non-Stationary MDPs
Yash Chandak, Georgios Theocharous, Shiv Shankar, Martha White, Sridhar Mahadevan, Philip Thomas
Poster
Tue 8:00 Learning Adversarial Markov Decision Processes with Bandit Feedback and Unknown Transition
Chi Jin, Tiancheng Jin, Haipeng Luo, Suvrit Sra, Tiancheng Yu
Poster
Tue 8:00 Working Memory Graphs
Ricky Loynd, Roland Fernandez, Asli Celikyilmaz, Adith Swaminathan, Matthew Hausknecht
Poster
Tue 8:00 Generative Adversarial Imitation Learning with Neural Network Parameterization: Global Optimality and Convergence Rate
Yufeng Zhang, Qi Cai, Zhuoran Yang, Zhaoran Wang
Poster
Tue 8:00 Learning Fair Policies in Multi-Objective (Deep) Reinforcement Learning with Average and Discounted Rewards
Umer Siddique, Paul Weng, Matthieu Zimmer
Poster
Tue 8:00 Discount Factor as a Regularizer in Reinforcement Learning
Ron Amit, Ron Meir, Kamil Ciosek
Poster
Tue 8:00 Batch Reinforcement Learning with Hyperparameter Gradients
Byung-Jun Lee, Jongmin Lee, Peter Vrancx, Dongho Kim, Kee-Eung Kim
Poster
Tue 8:00 Representations for Stable Off-Policy Reinforcement Learning
Dibya Ghosh, Marc Bellemare
Poster
Tue 8:00 GradientDICE: Rethinking Generalized Offline Estimation of Stationary Values
Shangtong Zhang, Bo Liu, Shimon Whiteson
Poster
Tue 8:00 FormulaZero: Distributionally Robust Online Adaptation via Offline Population Synthesis
Aman Sinha, Matthew O'Kelly, Hongrui Zheng, Rahul Mangharam, John Duchi, Russ Tedrake
Poster
Tue 9:00 Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic Reasoning
Qing Li, Siyuan Huang, Yining Hong, Yixin Chen, Ying Nian Wu, Song-Chun Zhu
Poster
Tue 9:00 Description Based Text Classification with Reinforcement Learning
Duo Chai, Wei Wu, Qinghong Han, Fei Wu, Jiwei Li
Poster
Tue 9:00 Learning Compound Tasks without Task-specific Knowledge via Imitation and Self-supervised Learning
Sang-Hyun Lee, Seung-Woo Seo
Poster
Tue 9:00 Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences
Daniel Brown, Russell Coleman, Ravi Srinivasan, Scott Niekum
Poster
Tue 9:00 Enhanced POET: Open-ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their Solutions
Rui Wang, Joel Lehman, Aditya Rawal, Jiale Zhi, Yulun Li, Jeffrey Clune, Ken Stanley
Poster
Tue 9:00 Hierarchically Decoupled Imitation For Morphological Transfer
Donald Hejna, Lerrel Pinto, Pieter Abbeel
Poster
Tue 9:00 A Markov Decision Process Model for Socio-Economic Systems Impacted by Climate Change
Salman Sadiq Shuvo, Yasin Yilmaz, Alan Bush, Mark Hafen
Poster
Tue 9:00 Structured Policy Iteration for Linear Quadratic Regulator
Youngsuk Park, Ryan A. Rossi, Zheng Wen, Gang Wu, Handong Zhao
Poster
Tue 9:00 Variational Imitation Learning with Diverse-quality Demonstrations
Voot Tangkaratt, Bo Han, Emti Khan, Masashi Sugiyama
Poster
Tue 9:00 Evolutionary Reinforcement Learning for Sample-Efficient Multiagent Coordination
Somdeb Majumdar, Shauharda Khadka, Santiago Miret, Stephen Mcaleer, Kagan Tumer
Poster
Tue 9:00 Lookahead-Bounded Q-learning
Ibrahim El Shar, Daniel Jiang
Poster
Tue 9:00 Designing Optimal Dynamic Treatment Regimes: A Causal Reinforcement Learning Approach
Junzhe Zhang
Poster
Tue 9:00 Tightening Exploration in Upper Confidence Reinforcement Learning
Hippolyte Bourel, Odalric-Ambrym Maillard, Mohammad Sadegh Talebi
Poster
Tue 10:00 Policy Teaching via Environment Poisoning: Training-time Adversarial Attacks against Reinforcement Learning
Amin Rakhsha, Goran Radanovic, Rati Devidze, Jerry Zhu, Adish Singla
Poster
Tue 10:00 Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning
Zhaohan Guo, Bernardo Avila Pires, Bilal Piot, Jean-Bastien Grill, Florent Altché, Remi Munos, Mohammad Gheshlaghi Azar
Poster
Tue 10:00 Global Concavity and Optimization in a Class of Dynamic Discrete Choice Models
Yiding Feng, Ekaterina Khmelnitskaya, Denis Nekipelov
Poster
Tue 10:00 Responsive Safety in Reinforcement Learning by PID Lagrangian Methods
Adam Stooke, Joshua Achiam, Pieter Abbeel
Poster
Tue 10:00 Selective Dyna-style Planning Under Limited Model Capacity
Zaheer Abbas, Samuel Sokota, Erin Talvitie, Martha White
Poster
Tue 10:00 Optimally Solving Two-Agent Decentralized POMDPs Under One-Sided Information Sharing
Yuxuan Xie, Jilles Dibangoye, Olivier Buffet
Poster
Tue 10:00 Logarithmic Regret for Adversarial Online Control
Dylan Foster, Max Simchowitz
Poster
Tue 10:00 Sub-Goal Trees -- a Framework for Goal-Based Reinforcement Learning
Tom Jurgenson, Or Avner, Edward Groshev, Aviv Tamar
Poster
Tue 10:00 Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data
Felipe Petroski Such, Aditya Rawal, Joel Lehman, Ken Stanley, Jeffrey Clune
Poster
Tue 11:00 Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills
Victor Campos, Alexander Trott, Caiming Xiong, Richard Socher, Xavier Giro-i-Nieto, Jordi Torres
Poster
Tue 11:00 Domain Adaptive Imitation Learning
Kuno Kim, Yihong Gu, Jiaming Song, Shengjia Zhao, Stefano Ermon
Poster
Tue 11:00 Stochastically Dominant Distributional Reinforcement Learning
John Martin, Michal Lyskawinski, Xiaohu Li, Brendan Englot
Poster
Tue 12:00 Learning Portable Representations for High-Level Planning
Steve James, Benjamin Rosman, George Konidaris
Poster
Tue 12:00 Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics
Arsenii Kuznetsov, Pavel Shvechikov, Alexander Grishin, Dmitry Vetrov
Poster
Tue 12:00 A distributional view on multi-objective policy optimization
Abbas Abdolmaleki, Sandy Huang, Leonard Hasenclever, Michael Neunert, Francis Song, Martina Zambelli, Murilo Martins, Nicolas Heess, Raia Hadsell, Martin Riedmiller
Poster
Tue 12:00 Understanding the Curse of Horizon in Off-Policy Evaluation via Conditional Importance Sampling
Yao Liu, Pierre-Luc Bacon, Emma Brunskill
Poster
Tue 12:00 Multi-step Greedy Reinforcement Learning Algorithms
Manan Tomar, Yonathan Efroni, Mohammad Ghavamzadeh
Poster
Tue 12:00 Ready Policy One: World Building Through Active Learning
Philip Ball, Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromanski, Stephen Roberts
Poster
Tue 13:00 Generalization to New Actions in Reinforcement Learning
Ayush Jain, Andrew Szot, Joseph Lim
Poster
Tue 13:00 Learning with Good Feature Representations in Bandits and in RL with a Generative Model
Tor Lattimore, Csaba Szepesvari, Gellért Weisz
Poster
Tue 13:00 Sample Factory: Egocentric 3D Control from Pixels at 100000 FPS with Asynchronous Reinforcement Learning
Aleksei Petrenko, Zhehui Huang, Tushar Kumar, Gaurav Sukhatme, Vladlen Koltun
Poster
Tue 13:00 Sequential Transfer in Reinforcement Learning with a Generative Model
Andrea Tirinzoni, Riccardo Poiani, Marcello Restelli
Poster
Tue 13:00 Growing Action Spaces
Gregory Farquhar, Laura Gustafson, Zeming Lin, Shimon Whiteson, Nicolas Usunier, Gabriel Synnaeve
Poster
Tue 14:00 OPtions as REsponses: Grounding behavioural hierarchies in multi-agent reinforcement learning
Sasha Vezhnevets, Yuhuai Wu, Maria Eckstein, Rémi Leblond, Joel Z Leibo
Poster
Tue 14:00 Logarithmic Regret for Learning Linear Quadratic Regulators Efficiently
Asaf Cassel, Alon Cohen, Tomer Koren
Poster
Tue 14:00 Knowing The What But Not The Where in Bayesian Optimization
Vu Nguyen, Michael A Osborne
Poster
Tue 15:00 Thompson Sampling Algorithms for Mean-Variance Bandits
Qiuyu Zhu, Vincent Tan
Poster
Tue 15:00 Double Reinforcement Learning for Efficient and Robust Off-Policy Evaluation
Nathan Kallus, Masatoshi Uehara
Poster
Tue 15:00 Invariant Causal Prediction for Block MDPs
Amy Zhang, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup
Poster
Tue 18:00 Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems
Kaixuan Wei, Angelica I Aviles-Rivero, Jingwei Liang, Ying Fu, Carola-Bibiane Schönlieb, Hua Huang
Poster
Tue 18:00 Striving for Simplicity and Performance in Off-Policy DRL: Output Normalization and Non-Uniform Sampling
Che Wang, Yanqiu Wu, Quan Vuong, Keith Ross
Poster
Tue 18:00 Can Increasing Input Dimensionality Improve Deep Reinforcement Learning?
Kei Ota, Tomoaki Oiki, Devesh Jha, Toshisada Mariyama, Daniel Nikovski
Poster
Tue 18:00 Intrinsic Reward Driven Imitation Learning via Generative Model
Xingrui Yu, Yueming LYU, Ivor Tsang
Poster
Wed 5:00 Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Control
Jie Xu, Yunsheng Tian, Pingchuan Ma, Daniela Rus, Shinjiro Sueda, Wojciech Matusik
Poster
Wed 5:00 Implicit Generative Modeling for Efficient Exploration
Neale Ratzlaff, Qinxun Bai, Fuxin Li, Wei Xu
Poster
Wed 5:00 An Optimistic Perspective on Offline Deep Reinforcement Learning
Rishabh Agarwal, Dale Schuurmans, Mohammad Norouzi
Poster
Wed 5:00 Best Arm Identification for Cascading Bandits in the Fixed Confidence Setting
Zixin Zhong, Wang Chi Cheung, Vincent Tan
Poster
Wed 5:00 Adaptive Estimator Selection for Off-Policy Evaluation
Yi Su, Pavithra Srinath, Akshay Krishnamurthy
Poster
Wed 5:00 Stabilizing Transformers for Reinforcement Learning
Emilio Parisotto, Francis Song, Jack Rae, Razvan Pascanu, Caglar Gulcehre, Siddhant Jayakumar, Max Jaderberg, Raphael Lopez Kaufman, Aidan Clark, Seb Noury, Matthew Botvinick, Nicolas Heess, Raia Hadsell
Poster
Wed 5:00 Learning What to Defer for Maximum Independent Sets
Sungsoo Ahn, Younggyo Seo, Jinwoo Shin
Poster
Wed 5:00 Adaptive Droplet Routing in Digital Microfluidic Biochips Using Deep Reinforcement Learning
Tung-Che Liang, Zhanwei Zhong, Yaas Bigdeli, Tsung-Yi Ho, Krishnendu Chakrabarty, Richard Fair
Poster
Wed 5:00 What can I do here? A Theory of Affordances in Reinforcement Learning
Khimya Khetarpal, Zafarali Ahmed, Gheorghe Comanici, Dave Abel, Doina Precup
Poster
Wed 5:00 Reinforcement Learning for Integer Programming: Learning to Cut
Yunhao Tang, Shipra Agrawal, Yuri Faenza
Poster
Wed 8:00 Identifying the Reward Function by Anchor Actions
Sinong Geng, Houssam Nassif, Charlie Manzanares, Max Reppen, Ronnie Sircar
Poster
Wed 8:00 Planning to Explore via Self-Supervised World Models
Ramanan Sekar, Oleg Rybkin, Kostas Daniilidis, Pieter Abbeel, Danijar Hafner, Deepak Pathak
Poster
Wed 8:00 Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings
Jesse Zhang, Brian Cheung, Chelsea Finn, Sergey Levine, Dinesh Jayaraman
Poster
Wed 8:00 Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning
Kimin Lee, Younggyo Seo, Seunghyun Lee, Honglak Lee, Jinwoo Shin
Poster
Wed 8:00 Learning to Score Behaviors for Guided Policy Optimization
Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang, Krzysztof Choromanski, Anna Choromanska, Michael Jordan
Poster
Wed 8:00 Reinforcement Learning for Non-Stationary Markov Decision Processes: The Blessing of (More) Optimism
Wang Chi Cheung, David Simchi-Levi, Ruihao Zhu
Poster
Wed 9:00 Flexible and Efficient Long-Range Planning Through Curious Exploration
Aidan Curtis, Minjian Xin, Dilip Arumugam, Kevin Feigelis, Daniel Yamins
Poster
Wed 9:00 Accountable Off-Policy Evaluation With Kernel Bellman Statistics
Yihao Feng, Tongzheng Ren, Ziyang Tang, Qiang Liu
Poster
Wed 9:00 Leveraging Procedural Generation to Benchmark Reinforcement Learning
Karl Cobbe, Chris Hesse, Jacob Hilton, John Schulman
Poster
Wed 9:00 Hallucinative Topological Memory for Zero-Shot Visual Planning
Kara Liu, Thanard Kurutach, Christine Tung, Pieter Abbeel, Aviv Tamar
Poster
Wed 9:00 Provable Self-Play Algorithms for Competitive Reinforcement Learning
Yu Bai, Chi Jin
Poster
Wed 10:00 Data Valuation using Reinforcement Learning
Jinsung Yoon, Sercan Arik, Tomas Pfister
Poster
Wed 10:00 A Game Theoretic Framework for Model Based Reinforcement Learning
Aravind Rajeswaran, Igor Mordatch, Vikash Kumar
Poster
Wed 10:00 Fast computation of Nash Equilibria in Imperfect Information Games
Remi Munos, Julien Perolat, Jean-Baptiste Lespiau, Mark Rowland, Bart De Vylder, Marc Lanctot, Finbarr Timbers, Daniel Hennes, Shayegan Omidshafiei, Audrunas Gruslys, Mohammad Gheshlaghi Azar, Edward Lockhart, Karl Tuyls
Poster
Wed 10:00 Provable Representation Learning for Imitation Learning via Bi-level Optimization
Sanjeev Arora, Simon Du, Sham Kakade, Yuping Luo, Nikunj Saunshi
Poster
Wed 10:00 Efficiently Solving MDPs with Stochastic Mirror Descent
Yujia Jin, Aaron Sidford
Poster
Wed 10:00 Batch Stationary Distribution Estimation
Junfeng Wen, Bo Dai, Lihong Li, Dale Schuurmans
Poster
Wed 11:00 A Finite-Time Analysis of Q-Learning with Neural Network Function Approximation
Pan Xu, Quanquan Gu
Poster
Wed 11:00 Learning Near Optimal Policies with Low Inherent Bellman Error
Andrea Zanette, Alessandro Lazaric, Mykel Kochenderfer, Emma Brunskill
Poster
Wed 11:00 “Other-Play” for Zero-Shot Coordination
Hengyuan Hu, Alexander Peysakhovich, Adam Lerer, Jakob Foerster
Poster
Wed 11:00 Revisiting Fundamentals of Experience Replay
William Fedus, Prajit Ramachandran, Rishabh Agarwal, Yoshua Bengio, Hugo Larochelle, Mark Rowland, Will Dabney
Poster
Wed 11:00 Option Discovery in the Absence of Rewards with Manifold Analysis
Amitay Bar, Ronen Talmon, Ron Meir
Poster
Wed 12:00 Inductive-bias-driven Reinforcement Learning For Efficient Schedules in Heterogeneous Clusters
Subho Banerjee, Saurabh Jha, Zbigniew Kalbarczyk, Ravishankar Iyer
Poster
Wed 12:00 Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions
Omer Gottesman, Joseph Futoma, Yao Liu, Sonali Parbhoo, Leo Celi, Emma Brunskill, Finale Doshi-Velez
Poster
Wed 12:00 Efficient Optimistic Exploration in Linear-Quadratic Regulators via Lagrangian Relaxation
Marc Abeille, Alessandro Lazaric
Poster
Wed 12:00 No-Regret Exploration in Goal-Oriented Reinforcement Learning
Jean Tarbouriech, Evrard Garcelon, Michal Valko, Matteo Pirotta, Alessandro Lazaric
Poster
Wed 12:00 Deep Coordination Graphs
Wendelin Boehmer, Vitaly Kurin, Shimon Whiteson
Poster
Wed 12:00 CoMic: Complementary Task Learning & Mimicry for Reusable Skills
Leonard Hasenclever, Fabio Pardo, Raia Hadsell, Nicolas Heess, Josh Merel
Poster
Wed 13:00 A Natural Lottery Ticket Winner: Reinforcement Learning with Ordinary Neural Circuits
Ramin Hasani, Mathias Lechner, Alexander Amini, Daniela Rus, Radu Grosu
Poster
Wed 13:00 Fast Adaptation to New Environments via Policy-Dynamics Value Functions
Roberta Raileanu, Max Goldstein, Arthur Szlam, Facebook Rob Fergus
Poster
Wed 13:00 Student-Teacher Curriculum Learning via Reinforcement Learning: Predicting Hospital Inpatient Admission Location
Rasheed El-Bouri, David Eyre, Peter Watkinson, Tingting Zhu, David Clifton
Poster
Wed 13:00 Interference and Generalization in Temporal Difference Learning
Emmanuel Bengio, Joelle Pineau, Doina Precup
Poster
Wed 14:00 Control Frequency Adaptation via Action Persistence in Batch Reinforcement Learning
Alberto Maria Metelli, Flavio Mazzolini, Lorenzo Bisi, Luca Sabbioni, Marcello Restelli
Poster
Wed 14:00 Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes
Chen-Yu Wei, Mehdi Jafarnia, Haipeng Luo, Hiteshi Sharma, Rahul Jain
Poster
Wed 15:00 Statistically Efficient Off-Policy Policy Gradients
Nathan Kallus, Masatoshi Uehara
Poster
Wed 15:00 Agent57: Outperforming the Atari Human Benchmark
Adrià Puigdomenech Badia, Bilal Piot, Steven Kapturowski, Pablo Sprechmann, Alex Vitvitskyi, Zhaohan Guo, Charles Blundell
Poster
Wed 16:00 Bidirectional Model-based Policy Optimization
Hang Lai, Jian Shen, Weinan Zhang, Yong Yu
Poster
Wed 16:00 Safe Reinforcement Learning in Constrained Markov Decision Processes
Akifumi Wachi, Yanan Sui
Poster
Wed 16:00 From Chaos to Order: Symmetry and Conservation Laws in Game Dynamics
Sai Ganesh Nagarajan, David Balduzzi, Georgios Piliouras
Poster
Thu 6:00 Bridging the Gap Between f-GANs and Wasserstein GANs
Jiaming Song, Stefano Ermon
Poster
Thu 6:00 Stochastic Flows and Geometric Optimization on the Orthogonal Group
Krzysztof Choromanski, David Cheikhi, Jared Quincy Davis, Valerii Likhosherstov, Achille Nazaret, Achraf Bahamou, Xingyou Song, Mrugank Akarte, Jack Parker-Holder, Jacob Bergquist, Yuan Gao, Aldo Pacchiano, Tamas Sarlos, Adrian Weller, Vikas Sindhwani
Poster
Thu 6:00 On the Expressivity of Neural Networks for Deep Reinforcement Learning
Kefan Dong, Yuping Luo, Tianhe (Kevin) Yu, Chelsea Finn, Tengyu Ma
Poster
Thu 6:00 Learning Selection Strategies in Buchberger’s Algorithm
Dylan Peifer, Michael Stillman, Daniel Halpern-Leistner
Poster
Thu 6:00 History-Gradient Aided Batch Size Adaptation for Variance Reduced Algorithms
Kaiyi Ji, Zhe Wang, Bowen Weng, Yi Zhou, Wei Zhang, Yingbin LIANG
Poster
Thu 6:00 Estimating Q(s,s') with Deep Deterministic Dynamics Gradients
Ashley Edwards, Himanshu Sahni, Rosanne Liu, Jane Hung, Ankit Jain, Rui Wang, Adrien Ecoffet, Thomas Miconi, Charles Isbell, Jason Yosinski
Poster
Thu 6:00 Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning
Silviu Pitis, Harris Chan, Stephen Zhao, Bradly Stadie, Jimmy Ba
Poster
Thu 6:00 Reward-Free Exploration for Reinforcement Learning
Chi Jin, Akshay Krishnamurthy, Max Simchowitz, Tiancheng Yu
Poster
Thu 6:00 Learning Robot Skills with Temporal Variational Inference
Tanmay Shankar, Abhinav Gupta
Poster
Thu 6:00 Constrained Markov Decision Processes via Backward Value Functions
Harsh Satija, Philip Amortila, Joelle Pineau
Poster
Thu 6:00 Deep Reinforcement Learning with Smooth Policy
Qianli Shen, Yan Li, Haoming Jiang, Zhaoran Wang, Tuo Zhao
Poster
Thu 6:00 GraphOpt: Learning Optimization Models of Graph Formation
Rakshit Trivedi, Jiachen Yang, Hongyuan Zha
Poster
Thu 6:00 Minimax-Optimal Off-Policy Evaluation with Linear Function Approximation
Yaqi Duan, Zeyu Jia, Mengdi Wang
Poster
Thu 6:00 Skew-Fit: State-Covering Self-Supervised Reinforcement Learning
Vitchyr Pong, Murtaza Dalal, Steven Lin, Ashvin Nair, Shikhar Bahl, Sergey Levine
Poster
Thu 6:00 Reducing Sampling Error in Batch Temporal Difference Learning
Brahma Pavse, Ishan Durugkar, Josiah Hanna, Peter Stone
Poster
Thu 6:00 Bandits for BMO Functions
Tianyu Wang, Cynthia Rudin
Poster
Thu 6:00 Provably Efficient Model-based Policy Adaptation
Yuda Song, Aditi Mavalankar, Wen Sun, Sicun Gao
Poster
Thu 7:00 Breaking the Curse of Many Agents: Provable Mean Embedding Q-Iteration for Mean-Field Reinforcement Learning
Lingxiao Wang, Zhuoran Yang, Zhaoran Wang
Poster
Thu 7:00 Clinician-in-the-Loop Decision Making: Reinforcement Learning with Near-Optimal Set-Valued Policies
Shengpu Tang, Aditya Modi, Michael Sjoding, Jenna Wiens
Poster
Thu 7:00 ConQUR: Mitigating Delusional Bias in Deep Q-Learning
DiJia Su, Jayden Ooi, Tyler Lu, Dale Schuurmans, Craig Boutilier
Poster
Thu 7:00 Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound
Lin Yang, Mengdi Wang
Poster
Thu 7:00 Goal-Aware Prediction: Learning to Model What Matters
Suraj Nair, Silvio Savarese, Chelsea Finn
Poster
Thu 7:00 Online Learned Continual Compression with Adaptive Quantization Modules
Lucas Caccia, Eugene Belilovsky, Massimo Caccia, Joelle Pineau
Poster
Thu 7:00 Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning
Dipendra Kumar Misra, Mikael Henaff, Akshay Krishnamurthy, John Langford
Poster
Thu 7:00 Adaptive Reward-Poisoning Attacks against Reinforcement Learning
Xuezhou Zhang, Yuzhe Ma, Adish Singla, Jerry Zhu
Poster
Thu 7:00 Model-Based Reinforcement Learning with Value-Targeted Regression
Alex Ayoub, Zeyu Jia, Csaba Szepesvari, Mengdi Wang, Lin Yang
Poster
Thu 7:00 R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games
Zhongxiang Dai, Yizhou Chen, Bryan Kian Hsiang Low, Patrick Jaillet , Teck-Hua Ho
Poster
Thu 8:00 An Imitation Learning Approach for Cache Replacement
Evan Liu, Milad Hashemi, Kevin Swersky, Partha Ranganathan, Junwhan Ahn
Poster
Thu 8:00 One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Control
Wenlong Huang, Igor Mordatch, Deepak Pathak
Poster
Thu 8:00 Provably Convergent Two-Timescale Off-Policy Actor-Critic with Function Approximation
Shangtong Zhang, Bo Liu, Hengshuai Yao, Shimon Whiteson
Poster
Thu 8:00 Momentum-Based Policy Gradient Methods
Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang
Poster
Thu 8:00 Gradient Temporal-Difference Learning with Regularized Corrections
Sina Ghiassian, Andrew Patterson, Shivam Garg, Dhawal Gupta, Adam White, Martha White
Poster
Thu 8:00 AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation
Jae Hyun Lim, Aaron Courville, Christopher Pal, Chin-Wei Huang
Poster
Thu 8:00 Learning Human Objectives by Evaluating Hypothetical Behavior
Siddharth Reddy, Anca Dragan, Sergey Levine, Shane Legg, Jan Leike
Poster
Thu 8:00 Optimizing Data Usage via Differentiable Rewards
Xinyi Wang, Hieu Pham, Paul Michel, Antonios Anastasopoulos, Jaime Carbonell, Graham Neubig
Poster
Thu 9:00 Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions
Michael Chang, Sid Kaushik, S. Matthew Weinberg, Thomas Griffiths, Sergey Levine
Poster
Thu 9:00 Active World Model Learning in Agent-rich Environments with Progress Curiosity
Kuno Kim, Megumi Sano, Julian De Freitas, Nick Haber, Daniel Yamins
Poster
Thu 9:00 On the Global Convergence Rates of Softmax Policy Gradient Methods
Jincheng Mei, Chenjun Xiao, Csaba Szepesvari, Dale Schuurmans
Poster
Thu 9:00 ROMA: Multi-Agent Reinforcement Learning with Emergent Roles
Tonghan Wang, Heng Dong, Victor Lesser, Chongjie Zhang
Poster
Thu 9:00 CURL: Contrastive Unsupervised Representations for Reinforcement Learning
Michael Laskin, Aravind Srinivas, Pieter Abbeel
Poster
Thu 9:00 Inferring DQN structure for high-dimensional continuous control
Andrey Sakryukin, Chedy Raissi, Mohan Kankanhalli
Poster
Thu 9:00 Symbolic Network: Generalized Neural Policies for Relational MDPs
Sankalp Garg, Aniket Bajpai, Mausam
Poster
Thu 9:00 Learning to Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning
Sai Krishna Gottipati, Boris Sattarov, Sufeng Niu, Yashaswi Pathak, Haoran Wei, Shengchao Liu, Shengchao Liu, Simon Blackburn, Karam Thomas, Connor Coley, Jian Tang, Sarath Chandar, Yoshua Bengio
Poster
Thu 12:00 Predictive Coding for Locally-Linear Control
Rui Shu, Tung Nguyen, Yinlam Chow, Tuan Pham, Khoat Than, Mohammad Ghavamzadeh, Stefano Ermon, Hung Bui
Poster
Thu 12:00 Monte-Carlo Tree Search as Regularized Policy Optimization
Jean-Bastien Grill, Florent Altché, Yunhao Tang, Thomas Hubert, Michal Valko, Ioannis Antonoglou, Remi Munos
Poster
Thu 12:00 Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules
Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio
Poster
Thu 12:00 Naive Exploration is Optimal for Online LQR
Max Simchowitz, Dylan Foster
Poster
Thu 12:00 Near-optimal Regret Bounds for Stochastic Shortest Path
Aviv Rosenberg, Alon Cohen, Yishay Mansour, Haim Kaplan
Poster
Thu 14:00 Reinforcement Learning for Molecular Design Guided by Quantum Mechanics
Gregor Simm, Robert Pinsler, Jose Miguel Hernandez-Lobato
Poster
Thu 14:00 Optimistic Policy Optimization with Bandit Feedback
Lior Shani, Yonathan Efroni, Aviv Rosenberg, Shie Mannor
Poster
Thu 14:00 Probing Emergent Semantics in Predictive Agents via Question Answering
Abhishek Das, Federico Carnevale, Hamza Merzic, Laura Rimell, Rosalia Schneider, Josh Abramson, Alden Hung, Arun Ahuja, Stephen Clark, Greg Wayne, Feilx Hill
Poster
Thu 14:00 Multi-Agent Determinantal Q-Learning
Yaodong Yang, Ying Wen, Jun Wang, Liheng Chen, Kun Shao, David Mguni, Weinan Zhang
Poster
Thu 15:00 Off-Policy Actor-Critic with Shared Experience Replay
Simon Schmitt, Matteo Hessel, Karen Simonyan
Poster
Thu 17:00 Self-Attentive Associative Memory
Hung Le, Truyen Tran, Svetha Venkatesh
Poster
Thu 17:00 Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making
Chengchun Shi, Runzhe Wan, Rui Song, Wenbin Lu, Ling Leng
Poster
Thu 17:00 Minimax Weight and Q-Function Learning for Off-Policy Evaluation
Masatoshi Uehara, Jiawei Huang, Nan Jiang
Poster
Thu 18:00 Learning Efficient Multi-agent Communication: An Information Bottleneck Approach
Rundong Wang, Xu He, Runsheng Yu, Wei Qiu, Bo An, Zinovi Rabinovich
Workshop
Thu 23:45 XXAI: Extending Explainable AI Beyond Deep Models and Classifiers
Wojciech Samek, Andreas HOLZINGER, Ruth Fong, Taesup Moon, Klaus-robert Mueller
Workshop
Fri 2:00 Poster session 1
Workshop
Fri 4:00 Invited Talk 5: Sepp Hochreiter - XAI and Strategy Extraction via Reward Redistribution
Wojciech Samek
Workshop
Fri 5:00 Challenges in Deploying and Monitoring Machine Learning Systems
Alessandra Tosi, Nathan Korda, Neil Lawrence
Workshop
Fri 5:00 Workshop on AI for Autonomous Driving (AIAD)
Wei-Lun (Harry) Chao, Rowan McAllister, Adrien Gaidon, Li Erran Li, Sven Kreiss
Workshop
Fri 5:30 Invited Talk 8: Osbert Bastani - Interpretable, Robust, and Verifiable Reinforcement Learning
Wojciech Samek
Workshop
Fri 5:30 OtoWorld: Towards Learning to Separate by Learning to Move
Omkar Ranadive
Workshop
Fri 6:15 Object-Oriented Learning: Perception, Representation, and Reasoning
Sungjin Ahn, Adam Kosiorek, Jessica Hamrick, Sjoerd van Steenkiste, Yoshua Bengio
Workshop
Fri 6:15 Contributed Talk 4: Yau et al. - What did you think would happen? Explaining Agent Behaviour through Intended Outcomes
Wojciech Samek
Workshop
Fri 6:30 Theoretical Foundations of Reinforcement Learning
Emma Brunskill, Thodoris Lykouris, Max Simchowitz, Wen Sun, Mengdi Wang
Workshop
Fri 6:30 Poster Session 2
Wojciech Samek
Workshop
Fri 6:30 Exploration, Policy Gradient Methods, and the Deadly Triad - Sham Kakade
Sham Kakade
Workshop
Fri 6:55 COVID-19 Applications: Integrating Logical Rules Into Neural Multi-Hop Reasoning for Drug Repurposing
Yushan Liu
Workshop
Fri 7:20 A Unifying View of Optimism in Episodic Reinforcement Learning - Gergely Neu
Gergely Neu
Workshop
Fri 8:35 Paper spotlight: Multi-agent Graph Reinforcement Learning for Connected Automated Driving
TIANYU SHI
Workshop
Fri 8:35 Paper Q&A session 1
Workshop
Fri 8:35 Paper spotlight: Autonomous Driving with Reinforcement Learning and Rule-based Policies
Amarildo Likmeta
Workshop
Fri 8:35 Paper spotlight: Learning Invariant Representations for Reinforcement Learning without Reconstruction
Amy Zhang
Workshop
Fri 8:35 Paper spotlight: Interpretable End-to-end Autonomous Driving with Reinforcement Learning
Jianyu Chen
Workshop
Fri 9:00 Poster Session (click to see links)
Workshop
Fri 10:40 Conservative Exploration in Bandits and Reinforcement Learning
Mohammad Ghavamzadeh
Workshop
Fri 11:20 Short Talk 1 - Crush Optimism with Pessimism: Structured Bandits Beyond Asymptotic Optimality
Kwang-Sung Jun
Workshop
Fri 11:30 Invited Talk: Claudia Clopath "Continual learning though consolidation – a neuroscience angle"
Claudia Clopath
Workshop
Fri 11:35 Short Talk 2 - Adaptive Discretization for Model-Based Reinforcement Learning
Sean Sinclair
Workshop
Fri 11:50 Counterfactual Data Augmentation using Locally Factored Dynamics
Silviu Pitis
Workshop
Fri 11:50 Short Talk 3 - A Kernel-Based Approach to Non-Stationary Reinforcement Learning in Metric Spaces
Omar Darwiche Domingues
Workshop
Fri 12:05 Spotlight Talk: Deep Reinforcement Learning amidst Lifelong Non-Stationarity
Workshop
Fri 12:20 Short Talk 5 - Near-Optimal Reinforcement Learning with Self-Play
Tiancheng Yu
Workshop
Fri 12:40 Invited Talk: Feedback in Imitation Learning: Confusion on Causality and Covariate Shift (Arun Venkatraman & Sanjiban Choudhury)
Sanjiban Choudhury, Arun Venkatraman
Workshop
Fri 14:15 Paper Q&A session 2
Workshop
Fri 14:20 Representation learning and exploration in reinforcement learning - Akshay Krishnamurthy
Akshay Krishnamurthy
Workshop
Sat 2:00 4th Lifelong Learning Workshop
Shagun Sodhani, Sarath Chandar, Balaraman Ravindran, Doina Precup
Workshop
Sat 2:15 Challenges & Opportunities in Lifelong Reinforcement Learning by Katja Hoffman
Katja Hofmann, Rika Antonova, Luisa Zintgraf
Workshop
Sat 3:00 Inductive Biases, Invariances and Generalization in Reinforcement Learning
Anirudh Goyal, Rosemary Nan Ke, Jane Wang, Theo Weber, Fabio Viola, Bernhard Schölkopf, Stefan Bauer
Workshop
Sat 4:00 Virtual Poster Session #1
Workshop
Sat 4:30 Invited talk 1 Silver
David Silver
Workshop
Sat 5:00 Negative Dependence and Submodularity: Theory and Applications in Machine Learning
Zelda Mariet, Michal Derezinski, Mike Gartrell
Workshop
Sat 5:15 Diversity in reinforcement learning
Takayuki Osogami
Workshop
Sat 5:45 Diversity in reinforcement learning
Workshop
Sat 5:50 Bridge Between Perception and Reasoning: Graph Neural Networks & Beyond
Jian Tang, Le Song, Jure Leskovec, Renjie Liao, Yujia Li, Sanja Fidler, Richard Zemel, Russ Salakhutdinov
Workshop
Sat 5:50 Automatic Data Augmentation for Generalization in Reinforcement Learning
Roberta Raileanu
Workshop
Sat 6:00 Credit assignment and meta-learning in a single lifelong trial by Jürgen Schmidhuber
Jürgen Schmidhuber
Workshop
Sat 7:00 1st Workshop on Language in Reinforcement Learning (LaReL)
Nantas Nardelli, Jelena Luketina, Nantas Nardelli, Jakob Foerster, Victor Zhong, Jacob Andreas, Edward Grefenstette, Tim Rocktäschel
Workshop
Sat 7:15 The NetHack Learning Environment
Tim Rocktäschel
Workshop
Sat 7:15 Invited Talk: Lifelong Learning: Towards Broad and Robust AI by Irina Rish
Irina Rish
Workshop
Sat 7:25 1.16 Learning to Prune Deep Neural Networks via Reinforcement Learning
Manas Gupta
Workshop
Sat 7:45 Open-ended environments for advancing RL
Max Jaderberg
Workshop
Sat 8:00 Incentives in Machine Learning
Boi Faltings, Yang Liu, David Parkes, Goran Radanovic, Dawn Song
Workshop
Sat 8:00 Virtual Poster Session #2
Workshop
Sat 8:05 Lightning Talks Session 1
Zhaohui Yang, Angel Navia-Vázquez, KUN LI, Hajime Ono, Yang Liu, Yuejiao Sun, Shahab Asoodeh, Chihoon Hwang, Romuald Menuet
Workshop
Sat 8:50 Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers
Swapnil Asawa, Benjamin Eysenbach
Workshop
Sat 9:00 Contributed Talk: Deep Reinforcement Learning amidst Lifelong Non-Stationarity
Annie Xie
Workshop
Sat 9:10 Machine Learning for Media Discovery
Erik Schmidt, Oriol Nieto, Fabien Gouyon, Yves Raimond, Katherine Kinnaird, Gert Lanckriet
Workshop
Sat 9:30 The FOAK Cycle for Model-based Life-long Learning by Rich Sutton
Richard Sutton
Workshop
Sat 10:45 Invited Talk: Karthik Narasimhan
Karthik Narasimhan
Workshop
Sat 11:15 Invited Talk: Yoav Artzi
Yoav Artzi
Workshop
Sat 12:10 Afternoon Poster Session
Workshop
Sat 13:00 Invited Talk: Marc-Alexandre Côté
Marc-Alexandre Côté
Workshop
Sat 14:00 Keynote Session 5: Advances and Open Problems in Federated Learning, by Brendan McMahan (Google)
Brendan McMahan
Workshop
Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels
Ilya Kostrikov
Workshop
(#101 / Sess. 1) Graph neural induction of value iteration
Andreea Deac
Workshop
Meta-Reinforcement Learning for Robotic Industrial Insertion Tasks
Gerrit Schoettler
Workshop
Bridging Worlds in Reinforcement Learning with Model-Advantage
Ashwin Kalyan, Nirbhay Modhe
Workshop
Watch your Weight Reinforcement Learning
Robert Müller
Workshop
Reinforcement Learning Generalization with Surprise Minimization
Jerry Zikun Chen
Workshop
Multi-Task Reinforcement Learning as a Hidden-Parameter Block MDP
Amy Zhang
Workshop
Model-based Adversarial Meta-Reinforcement Learning
Tengyu Ma, Zichuan Lin
Workshop
Deep Reinforcement Learning amidst Lifelong Non-Stationarity
Workshop
UNCLEAR: A Straightforward Method for Continual Reinforcement Learning
Workshop
Meta-Reinforcement Learning Robust to Distributional Shift via Model Identification and Experience Relabeling
Russell Mendonca
Workshop
Learning Invariant Representations for Reinforcement Learning without Reconstruction
Amy Zhang
Workshop
Group Equivariant Deep Reinforcement Learning
Arnab Kumar Mondal
Workshop
Continual Reinforcement Learning with Multi-Timescale Replay
Workshop
Towards Self-Paced Context Evaluation for Contextual Reinforcement Learning
Theresa Eimer
Workshop
DisCor: Corrective Feedback in Reinforcement Learning via Distribution Correction
Aviral Kumar
Workshop
Accepted Papers
Workshop
Nesterov Momentum Adversarial Perturbations in the Deep Reinforcement Learning Domain
Ezgi Korkmaz
Workshop
Exact (Then Approximate) Dynamic Programming for Deep Reinforcement Learning
Henrik Marklund
Workshop
Robust Reinforcement Learning using Adversarial Populations
Eugene Vinitsky
Workshop
Conditioning of Reinforcement Learning Agents and its Policy Regularization Application
Arip Asadulaev