More from the Same Authors

• 2020 : GANterpretations »
  Pablo Samuel Castro
• 2020 : Paper 19: Multiagent Driving Policy for Congestion Reduction in a Large Scale Scenario »
  Jiaxun Cui · Peter Stone
• 2021 : Task-Independent Causal State Abstraction »
  Zizhao Wang · Xuesu Xiao · Yuke Zhu · Peter Stone
• 2021 : Leveraging Information about Background Music in Human-Robot Interaction »
  Elad Liebman · Peter Stone
• 2021 : Lifting the veil on hyper-parameters for value-baseddeep reinforcement learning »
  João Madeira Araújo · Johan Obando Ceron · Pablo Samuel Castro
• 2021 : Lifting the veil on hyper-parameters for value-baseddeep reinforcement learning »
  João Madeira Araújo · Johan Obando Ceron · Pablo Samuel Castro
• 2021 : Safe Evaluation For Offline Learning: \\Are We Ready To Deploy? »
  Hager Radi · Josiah Hanna · Peter Stone · Matthew Taylor
• 2021 : Safe Evaluation For Offline Learning: \\Are We Ready To Deploy? »
  Hager Radi · Josiah Hanna · Peter Stone · Matthew Taylor
• 2022 : BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach »
  Mao Ye · Bo Liu · Stephen Wright · Peter Stone · Qiang Liu
• 2022 : Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks »
  Jesse Farebrother · Joshua Greaves · Rishabh Agarwal · Charline Le Lan · Ross Goroshin · Pablo Samuel Castro · Marc Bellemare
• 2022 : Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks »
  Jesse Farebrother · Joshua Greaves · Rishabh Agarwal · Charline Le Lan · Ross Goroshin · Pablo Samuel Castro · Marc Bellemare
• 2022 : ABC: Adversarial Behavioral Cloning for Offline Mode-Seeking Imitation Learning »
  Eddy Hudson · Ishan Durugkar · Garrett Warnell · Peter Stone
• 2022 : ABC: Adversarial Behavioral Cloning for Offline Mode-Seeking Imitation Learning »
  Eddy Hudson · Ishan Durugkar · Garrett Warnell · Peter Stone
• 2022 : Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks »
  Jesse Farebrother · Joshua Greaves · Rishabh Agarwal · Charline Le Lan · Ross Goroshin · Pablo Samuel Castro · Marc Bellemare
• 2022 : Variance Double-Down: The Small Batch Size Anomaly in Multistep Deep Reinforcement Learning »
  Johan Obando Ceron · Marc Bellemare · Pablo Samuel Castro
• 2022 : Panel RL Theory-Practice Gap »
  Peter Stone · Matej Balog · Jonas Buchli · Jason Gauci · Dhruv Madeka
• 2022 Workshop: Broadening Research Collaborations »
  Sara Hooker · Rosanne Liu · Pablo Samuel Castro · FatemehSadat Mireshghallah · Sunipa Dev · Benjamin Rosman · João Madeira Araújo · Savannah Thais · Sara Hooker · Sunny Sanyal · Tejumade Afonja · Swapneel Mehta · Tyler Zhu
• 2022 : Invited talk: Outracing Champion Gran Turismo Drivers with Deep Reinforcement Learning »
  Peter Stone
• 2022 : Human in the Loop Learning for Robot Navigation and Task Learning from Implicit Human Feedback »
  Peter Stone
• 2022 Poster: Reincarnating Reinforcement Learning: Reusing Prior Computation to Accelerate Progress »
  Rishabh Agarwal · Max Schwarzer · Pablo Samuel Castro · Aaron Courville · Marc Bellemare
• 2022 Poster: BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach »
  Bo Liu · Mao Ye · Stephen Wright · Peter Stone · Qiang Liu
• 2022 Poster: Value Function Decomposition for Iterative Design of Reinforcement Learning Agents »
  James MacGlashan · Evan Archer · Alisa Devlic · Takuma Seno · Craig Sherstan · Peter Wurman · Peter Stone
• 2021 : Q&A for Minmin Chen »
  Minmin Chen
• 2021 : Offline RL for recommendation systems »
  Minmin Chen
• 2021 : Invited Speaker Panel »
  Sham Kakade · Minmin Chen · Philip Thomas · Angela Schoellig · Barbara Engelhardt · Doina Precup · George Tucker
• 2021 : Invited Talk: Pablo Castro (Google Brain) on Estimating Policy Functions in Payment Systems using Reinforcement Learning »
  Pablo Samuel Castro
• 2021 Workshop: Ecological Theory of Reinforcement Learning: How Does Task Design Influence Agent Learning? »
  Manfred Díaz · Hiroki Furuta · Elise van der Pol · Lisa Lee · Shixiang (Shane) Gu · Pablo Samuel Castro · Simon Du · Marc Bellemare · Sergey Levine
• 2021 Poster: Adversarial Intrinsic Motivation for Reinforcement Learning »
  Ishan Durugkar · Mauricio Tec · Scott Niekum · Peter Stone
• 2021 Poster: Conflict-Averse Gradient Descent for Multi-task learning »
  Bo Liu · Xingchao Liu · Xiaojie Jin · Peter Stone · Qiang Liu
• 2021 Oral: Deep Reinforcement Learning at the Edge of the Statistical Precipice »
  Rishabh Agarwal · Max Schwarzer · Pablo Samuel Castro · Aaron Courville · Marc Bellemare
• 2021 Poster: Machine versus Human Attention in Deep Reinforcement Learning Tasks »
  Sihang Guo · Ruohan Zhang · Bo Liu · Yifeng Zhu · Dana Ballard · Mary Hayhoe · Peter Stone
• 2021 : Lifting the veil on hyper-parameters for value-baseddeep reinforcement learning »
  João Madeira Araújo · Johan Obando Ceron · Pablo Samuel Castro
• 2021 Poster: Deep Reinforcement Learning at the Edge of the Statistical Precipice »
  Rishabh Agarwal · Max Schwarzer · Pablo Samuel Castro · Aaron Courville · Marc Bellemare
• 2021 Poster: The Difficulty of Passive Learning in Deep Reinforcement Learning »
  Georg Ostrovski · Pablo Samuel Castro · Will Dabney
• 2021 Poster: MICo: Improved representations via sampling-based state similarity for Markov decision processes »
  Pablo Samuel Castro · Tyler Kastner · Prakash Panangaden · Mark Rowland
• 2020 : Contributed Talk #3: Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning »
  Rishabh Agarwal · Marlos C. Machado · Pablo Samuel Castro · Marc Bellemare
• 2020 : Contributed Talk 4: Addressing Extrapolation Error in Deep Offline Reinforcement Learning »
  Caglar Gulcehre
• 2020 : Q&A: Peter Stone (The University of Texas at Austin): Ad Hoc Autonomous Agent Teams: Collaboration without Pre-Coordination, with Natasha Jaques (Google) [moderator] »
  Peter Stone · Natasha Jaques
• 2020 : Invited Speaker: Peter Stone (The University of Texas at Austin) on Ad Hoc Autonomous Agent Teams: Collaboration without Pre-Coordination »
  Peter Stone
• 2020 : Panel discussion »
  Pierre-Yves Oudeyer · Marc Bellemare · Peter Stone · Matt Botvinick · Susan Murphy · Anusha Nagabandi · Ashley Edwards · Karen Liu · Pieter Abbeel
• 2020 : Discussion Panel »
  Pete Florence · Dorsa Sadigh · Carolina Parada · Jeannette Bohg · Roberto Calandra · Peter Stone · Fabio Ramos
• 2020 : Invited talk: Peter Stone "Grounded Simulation Learning for Sim2Real with Connections to Off-Policy Reinforcement Learning" »
  Peter Stone
• 2020 Poster: Critic Regularized Regression »
  Ziyu Wang · Alexander Novikov · Konrad Zolna · Josh Merel · Jost Tobias Springenberg · Scott Reed · Bobak Shahriari · Noah Siegel · Caglar Gulcehre · Nicolas Heess · Nando de Freitas
• 2020 Poster: Firefly Neural Architecture Descent: a General Approach for Growing Neural Networks »
  Lemeng Wu · Bo Liu · Peter Stone · Qiang Liu
• 2020 Poster: An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch »
  Siddharth Desai · Ishan Durugkar · Haresh Karnan · Garrett Warnell · Josiah Hanna · Peter Stone
• 2019 : Welcoming remarks and introduction »
  Levent Sagun · Caglar Gulcehre · Adriana Romero Soriano · Negar Rostamzadeh · Nando de Freitas
• 2019 Poster: Surrogate Objectives for Batch Policy Optimization in One-step Decision Making »
  Minmin Chen · Ramki Gummadi · Chris Harris · Dale Schuurmans
• 2019 Poster: A Geometric Perspective on Optimal Representations for Reinforcement Learning »
  Marc Bellemare · Will Dabney · Robert Dadashi · Adrien Ali Taiga · Pablo Samuel Castro · Nicolas Le Roux · Dale Schuurmans · Tor Lattimore · Clare Lyle
• 2018 : Peter Stone »
  Peter Stone
• 2018 : Control Algorithms for Imitation Learning from Observation »
  Peter Stone
• 2018 : Peter Stone »
  Peter Stone
• 2016 : Peter Stone (University of Texas at Austin) »
  Peter Stone
• 2015 Workshop: Learning, Inference and Control of Multi-Agent Systems »
  Vicenç Gómez · Gerhard Neumann · Jonathan S Yedidia · Peter Stone