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posters
Zhengxing Chen · Juan Jose Garau Luis · Ignacio Albert Smet · Aditya Modi · Sabina Tomkins · Riley Simmons-Edler · Hongzi Mao · Alexander Irpan · Hao Lu · Rose Wang · Subhojyoti Mukherjee · Aniruddh Raghu · Syed Arbab Mohd Shihab · Byung Hoon Ahn · Rasool Fakoor · Pratik Chaudhari · Elena Smirnova · Min-hwan Oh · Xiaocheng Tang · Tony Qin · Qingyang Li · Marc Brittain · Ian Fox · Supratik Paul · Xiaofeng Gao · Yinlam Chow · Gabriel Dulac-Arnold · Ofir Nachum · Nikos Karampatziakis · Bharathan Balaji · Supratik Paul · Ali Davody · Djallel Bouneffouf · Himanshu Sahni · Soo Kim · Andrey Kolobov · Alexander Amini · Yao Liu · Xinshi Chen · · Craig Boutilier
Author Information
Zhengxing Chen (Facebook)
Juan Jose Garau Luis (MIT)
Ignacio Albert Smet (Imperial College London)
Aditya Modi (University of Michigan)
Sabina Tomkins (Harvard University)
Riley Simmons-Edler (Princeton University)
Hongzi Mao (MIT)
Alexander Irpan (Google)
Hao Lu (Princeton University)
Rose Wang (MIT)
Subhojyoti Mukherjee (UMass Amherst)
Aniruddh Raghu (MIT)
Syed Arbab Mohd Shihab (Iowa State University)
Byung Hoon Ahn (University of California, San Diego)
Rasool Fakoor (Amazon AI)
Pratik Chaudhari (Amazon Web Services)
Elena Smirnova (Criteo)
Min-hwan Oh (Columbia University)
Xiaocheng Tang (Didi Chuxing)
Tony Qin (DiDi Research America)
Qingyang Li (Didi AI Labs)
Marc Brittain (Iowa State University)
Ian Fox (University of Michigan)
Supratik Paul (University of Oxford)
Xiaofeng Gao (UCLA)
Yinlam Chow (Google)
Gabriel Dulac-Arnold (Google Research)
Ofir Nachum (Google Brain)
Nikos Karampatziakis (Microsoft)
Bharathan Balaji (Amazon.com, Inc.)
I work on reinforcement learning in AWS AI Labs. We released an autonomous racing car called DeepRacer in 2018 along with 12 examples showcasing use of RL in different domains. I did my PhD from UC San Diego in Internet of Things, where I worked on Smart Buildings.
Supratik Paul (University of Oxford)
Ali Davody (Romanian Institute of Science and Technology)
Djallel Bouneffouf (IBM Research)
Himanshu Sahni (Georgia Institute of Technology)
Soo Kim (Lawrence Livermore National Laboratory)
Andrey Kolobov (Microsoft Research)
Alexander Amini (MIT)
Yao Liu (Stanford University)
Xinshi Chen (Georgia Institution of Technology)
Craig Boutilier (Google)
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2023 : Risk-Aware Image Generation by Estimating and Propagating Uncertainty »
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2023 Poster: Sequential Multi-Dimensional Self-Supervised Learning for Clinical Time Series »
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2023 Poster: Reinforcement Learning with History Dependent Dynamic Contexts »
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2023 Poster: Investigating the Role of Model-Based Learning in Exploration and Transfer »
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2022 Poster: Why Should I Trust You, Bellman? The Bellman Error is a Poor Replacement for Value Error »
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2022 Poster: Model Selection in Batch Policy Optimization »
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2022 Spotlight: Model Selection in Batch Policy Optimization »
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2021 : Spotlight »
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2021 Poster: Meta-Thompson Sampling »
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2021 Spotlight: Meta-Thompson Sampling »
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2021 Poster: Off-Policy Confidence Sequences »
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2021 Poster: Bootstrapping Fitted Q-Evaluation for Off-Policy Inference »
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2021 Spotlight: Bootstrapping Fitted Q-Evaluation for Off-Policy Inference »
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2021 Poster: Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning »
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2021 Poster: Offline Reinforcement Learning with Fisher Divergence Critic Regularization »
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2021 Poster: Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills »
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2021 Poster: Representation Matters: Offline Pretraining for Sequential Decision Making »
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2021 Spotlight: Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning »
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2021 Spotlight: Offline Reinforcement Learning with Fisher Divergence Critic Regularization »
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2020 Poster: Predictive Coding for Locally-Linear Control »
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2020 Poster: Clinician-in-the-Loop Decision Making: Reinforcement Learning with Near-Optimal Set-Valued Policies »
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2020 Poster: ConQUR: Mitigating Delusional Bias in Deep Q-Learning »
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2020 Poster: Estimating Q(s,s') with Deep Deterministic Dynamics Gradients »
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2020 Poster: A Natural Lottery Ticket Winner: Reinforcement Learning with Ordinary Neural Circuits »
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2020 Poster: Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions »
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2020 Poster: Understanding the Curse of Horizon in Off-Policy Evaluation via Conditional Importance Sampling »
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2020 Poster: Learning To Stop While Learning To Predict »
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2020 Poster: Online Learning for Active Cache Synchronization »
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2020 Poster: Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach »
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2019 : Networking Lunch (provided) + Poster Session »
Abraham Stanway · Alex Robson · Aneesh Rangnekar · Ashesh Chattopadhyay · Ashley Pilipiszyn · Benjamin LeRoy · Bolong Cheng · Ce Zhang · Chaopeng Shen · Christian Schroeder · Christian Clough · Clement DUHART · Clement Fung · Cozmin Ududec · Dali Wang · David Dao · di wu · Dimitrios Giannakis · Dino Sejdinovic · Doina Precup · Duncan Watson-Parris · Gege Wen · George Chen · Gopal Erinjippurath · Haifeng Li · Han Zou · Herke van Hoof · Hillary A Scannell · Hiroshi Mamitsuka · Hongbao Zhang · Jaegul Choo · James Wang · James Requeima · Jessica Hwang · Jinfan Xu · Johan Mathe · Jonathan Binas · Joonseok Lee · Kalai Ramea · Kate Duffy · Kevin McCloskey · Kris Sankaran · Lester Mackey · Letif Mones · Loubna Benabbou · Lynn Kaack · Matthew Hoffman · Mayur Mudigonda · Mehrdad Mahdavi · Michael McCourt · Mingchao Jiang · Mohammad Mahdi Kamani · Neel Guha · Niccolo Dalmasso · Nick Pawlowski · Nikola Milojevic-Dupont · Paulo Orenstein · Pedram Hassanzadeh · Pekka Marttinen · Ramesh Nair · Sadegh Farhang · Samuel Kaski · Sandeep Manjanna · Sasha Luccioni · Shuby Deshpande · Soo Kim · Soukayna Mouatadid · Sunghyun Park · Tao Lin · Telmo Felgueira · Thomas Hornigold · Tianle Yuan · Tom Beucler · Tracy Cui · Volodymyr Kuleshov · Wei Yu · yang song · Ydo Wexler · Yoshua Bengio · Zhecheng Wang · Zhuangfang Yi · Zouheir Malki -
2019 : panel discussion with Craig Boutilier (Google Research), Emma Brunskill (Stanford), Chelsea Finn (Google Brain, Stanford, UC Berkeley), Mohammad Ghavamzadeh (Facebook AI), John Langford (Microsoft Research) and David Silver (Deepmind) »
Peter Stone · Craig Boutilier · Emma Brunskill · Chelsea Finn · John Langford · David Silver · Mohammad Ghavamzadeh -
2019 : invited talk by Craig Boutilier (Google Research): Reinforcement Learning in Recommender Systems: Some Challenges »
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2019 Poster: Imitating Latent Policies from Observation »
Ashley Edwards · Himanshu Sahni · Yannick Schroecker · Charles Isbell -
2019 Poster: Combining parametric and nonparametric models for off-policy evaluation »
Omer Gottesman · Yao Liu · Scott Sussex · Emma Brunskill · Finale Doshi-Velez -
2019 Oral: Combining parametric and nonparametric models for off-policy evaluation »
Omer Gottesman · Yao Liu · Scott Sussex · Emma Brunskill · Finale Doshi-Velez -
2019 Oral: Imitating Latent Policies from Observation »
Ashley Edwards · Himanshu Sahni · Yannick Schroecker · Charles Isbell -
2019 Poster: Fingerprint Policy Optimisation for Robust Reinforcement Learning »
Supratik Paul · Michael A Osborne · Shimon Whiteson -
2019 Poster: DeepMDP: Learning Continuous Latent Space Models for Representation Learning »
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2019 Poster: Particle Flow Bayes' Rule »
Xinshi Chen · Hanjun Dai · Le Song -
2019 Poster: Generative Adversarial User Model for Reinforcement Learning Based Recommendation System »
Xinshi Chen · Shuang Li · Hui Li · Shaohua Jiang · Yuan Qi · Le Song -
2019 Poster: Beyond Backprop: Online Alternating Minimization with Auxiliary Variables »
Anna Choromanska · Benjamin Cowen · Sadhana Kumaravel · Ronny Luss · Mattia Rigotti · Irina Rish · Paolo DiAchille · Viatcheslav Gurev · Brian Kingsbury · Ravi Tejwani · Djallel Bouneffouf -
2019 Oral: Beyond Backprop: Online Alternating Minimization with Auxiliary Variables »
Anna Choromanska · Benjamin Cowen · Sadhana Kumaravel · Ronny Luss · Mattia Rigotti · Irina Rish · Paolo DiAchille · Viatcheslav Gurev · Brian Kingsbury · Ravi Tejwani · Djallel Bouneffouf -
2019 Oral: Fingerprint Policy Optimisation for Robust Reinforcement Learning »
Supratik Paul · Michael A Osborne · Shimon Whiteson -
2019 Oral: DeepMDP: Learning Continuous Latent Space Models for Representation Learning »
Carles Gelada · Saurabh Kumar · Jacob Buckman · Ofir Nachum · Marc Bellemare -
2019 Oral: Generative Adversarial User Model for Reinforcement Learning Based Recommendation System »
Xinshi Chen · Shuang Li · Hui Li · Shaohua Jiang · Yuan Qi · Le Song -
2019 Oral: Particle Flow Bayes' Rule »
Xinshi Chen · Hanjun Dai · Le Song -
2018 Poster: The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference »
Hao Lu · Yuan Cao · Junwei Lu · Han Liu · Zhaoran Wang -
2018 Oral: The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference »
Hao Lu · Yuan Cao · Junwei Lu · Han Liu · Zhaoran Wang -
2018 Poster: Smoothed Action Value Functions for Learning Gaussian Policies »
Ofir Nachum · Mohammad Norouzi · George Tucker · Dale Schuurmans -
2018 Poster: Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games? »
Maithra Raghu · Alexander Irpan · Jacob Andreas · Bobby Kleinberg · Quoc Le · Jon Kleinberg -
2018 Oral: Smoothed Action Value Functions for Learning Gaussian Policies »
Ofir Nachum · Mohammad Norouzi · George Tucker · Dale Schuurmans -
2018 Oral: Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games? »
Maithra Raghu · Alexander Irpan · Jacob Andreas · Bobby Kleinberg · Quoc Le · Jon Kleinberg -
2018 Poster: More Robust Doubly Robust Off-policy Evaluation »
Mehrdad Farajtabar · Yinlam Chow · Mohammad Ghavamzadeh -
2018 Poster: Path Consistency Learning in Tsallis Entropy Regularized MDPs »
Yinlam Chow · Ofir Nachum · Mohammad Ghavamzadeh -
2018 Oral: Path Consistency Learning in Tsallis Entropy Regularized MDPs »
Yinlam Chow · Ofir Nachum · Mohammad Ghavamzadeh -
2018 Oral: More Robust Doubly Robust Off-policy Evaluation »
Mehrdad Farajtabar · Yinlam Chow · Mohammad Ghavamzadeh -
2017 Poster: The Predictron: End-To-End Learning and Planning »
David Silver · Hado van Hasselt · Matteo Hessel · Tom Schaul · Arthur Guez · Tim Harley · Gabriel Dulac-Arnold · David Reichert · Neil Rabinowitz · Andre Barreto · Thomas Degris -
2017 Talk: The Predictron: End-To-End Learning and Planning »
David Silver · Hado van Hasselt · Matteo Hessel · Tom Schaul · Arthur Guez · Tim Harley · Gabriel Dulac-Arnold · David Reichert · Neil Rabinowitz · Andre Barreto · Thomas Degris -
2017 Poster: Gradient Coding: Avoiding Stragglers in Distributed Learning »
Rashish Tandon · Qi Lei · Alexandros Dimakis · Nikos Karampatziakis -
2017 Talk: Gradient Coding: Avoiding Stragglers in Distributed Learning »
Rashish Tandon · Qi Lei · Alexandros Dimakis · Nikos Karampatziakis -
2017 Poster: Logarithmic Time One-Against-Some »
Hal Daumé · Nikos Karampatziakis · John Langford · Paul Mineiro -
2017 Talk: Logarithmic Time One-Against-Some »
Hal Daumé · Nikos Karampatziakis · John Langford · Paul Mineiro