Amy Zhang

发表

A Dissection of Overfitting and Generalization in Continuous Reinforcement Learning pdf

Joelle Pineau, Nicolas Ballas, Amy Zhang, 2018, ArXiv.

Invariant Causal Prediction for Block MDPs pdf

Joelle Pineau, Doina Precup, Yarin Gal, 2020, ICML.

MODEL-BASED REINFORCEMENT LEARNING

Matthew E. Taylor, Joelle Pineau, R. Calandra, 2021 .

Stable Policy Optimization via Off-Policy Divergence Regularization

Pascal Vincent, Joelle Pineau, Amy Zhang, 2020, UAI.

Out-of-Distribution Generalization via Risk Extrapolation (REx)

Aaron C. Courville, Rémi Le Priol, J. Jacobsen, 2020, International Conference on Machine Learning.

Learning Invariant Representations for Reinforcement Learning without Reconstruction

S. Levine, Rowan McAllister, R. Calandra, 2020, ICLR.

Learning Robust State Abstractions for Hidden-Parameter Block MDPs

Joelle Pineau, Khimya Khetarpal, Shagun Sodhani, 2021, ICLR.

Denoised MDPs: Learning World Models Better Than the World Itself

A. Torralba, S. Du, Phillip Isola, 2022, ICML.

Denoised MDPs: Learning World Models Better Than the World Itself

A. Torralba, S. Du, Phillip Isola, 2022, ICML.

Bisimulation Makes Analogies in Goal-Conditioned Reinforcement Learning

S. Levine, Ashvin Nair, Amy Zhang, 2022, ICML.

Denoised MDPs: Learning World Models Better Than the World Itself

A. Torralba, S. Du, Phillip Isola, 2022, ICML.

AutoCAT: Reinforcement Learning for Automated Exploration of Cache Timing-Channel Attacks

Amy Zhang, H. Lee, G. Suh, 2022, ArXiv.

Online Decision Transformer

Amy Zhang, Qinqing Zheng, Aditya Grover, 2022, ICML.

VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training

Yecheng Jason Ma, Vikash Kumar, Amy Zhang, 2022, ArXiv.

Denoised MDPs: Learning World Models Better Than the World Itself

Amy Zhang, A. Torralba, S. Du, 2022, ICML.

Latent State Marginalization as a Low-cost Approach for Improving Exploration

Aaron C. Courville, Ricky T. Q. Chen, Y. Bengio, 2022, ArXiv.

LAD: Language Augmented Diffusion for Reinforcement Learning

Amy Zhang, Yujie Lu, Edwin Zhang, 2022, ArXiv.

Neural Constraint Satisfaction: Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement

S. Levine, T. Griffiths, Franziska Meier, 2023, ICLR.

Contrastive Distillation Is a Sample-Efficient Self-Supervised Loss Policy for Transfer Learning

Christopher T. Lengerich, Amy Zhang, Kurt Shuster, 2022, ArXiv.

Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability pdf

Sergey Levine, Ryan P. Adams, Aviral Kumar, 2021, NeurIPS.

Multi-Task Reinforcement Learning with Context-based Representations pdf

Joelle Pineau, Shagun Sodhani, Amy Zhang, 2021, ICML.

Out-of-Distribution Generalization via Risk Extrapolation (REx)

Aaron C. Courville, Ethan Caballero, Jörn-Henrik Jacobsen, 2020, ICML.

Improving Sample Efficiency in Model-Free Reinforcement Learning from Images

Joelle Pineau, Ilya Kostrikov, Rob Fergus, 2019, AAAI.

BC-IRL: Learning Generalizable Reward Functions from Demonstrations

Franziska Meier, Dhruv Batra, Amy Zhang, 2023, ICLR.

A Survey of Generalisation in Deep Reinforcement Learning

Edward Grefenstette, Amy Zhang, Tim Rocktaschel, 2021, ArXiv.

Language Control Diffusion: Efficiently Scaling through Space, Time, and Tasks

Amy Zhang, Yujie Lu, Edwin Zhang, 2022, 2210.15629.

Plan2Vec: Unsupervised Representation Learning by Latent Plans pdf

Joelle Pineau, Pieter Abbeel, Ge Yang, 2020, L4DC.

MBRL-Lib: A Modular Library for Model-based Reinforcement Learning pdf

Roberto Calandra, Brandon Amos, Nathan O. Lambert, 2021, ArXiv.

Bisimulation Makes Analogies in Goal-Conditioned Reinforcement Learning

Sergey Levine, Amy Zhang, S. Levine, 2022, International Conference on Machine Learning.

Natural Environment Benchmarks for Reinforcement Learning pdf

Joelle Pineau, Yuxin Wu, Amy Zhang, 2018, ArXiv.

Intervention Design for Effective Sim2Real Transfer pdf

Joelle Pineau, David Meger, Melissa Mozifian, 2020, ArXiv.

AutoCAT: Reinforcement Learning for Automated Exploration of Cache-Timing Attacks

Amy Zhang, G. Suh, Yuandong Tian, 2022, 2023 IEEE International Symposium on High-Performance Computer Architecture (HPCA).

Invariant Causal Prediction for Block MDPs

Doina Precup, Clare Lyle, Joelle Pineau, 2020, ICML.

Decoupling Dynamics and Reward for Transfer Learning pdf

Joelle Pineau, Amy Zhang, Harsh Satija, 2018, ICLR.

Latent State Marginalization as a Low-cost Approach for Improving Exploration

Aaron C. Courville, Ricky T. Q. Chen, Y. Bengio, 2022, ICLR.

Learning Causal State Representations of Partially Observable Environments pdf

Joelle Pineau, Kamyar Azizzadenesheli, Anima Anandkumar, 2019, ArXiv.

Block Contextual MDPs for Continual Learning pdf

Joelle Pineau, Franziska Meier, Shagun Sodhani, 2021, L4DC.

L EARNING R OBUST S TATE A BSTRACTIONS

Joelle Pineau, Amy Zhang, Khimya Khetarpal, 2021 .

Multi-Task Reinforcement Learning as a Hidden-Parameter Block MDP pdf

Joelle Pineau, Khimya Khetarpal, Amy Zhang, 2020, ArXiv.

VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training

Yecheng Jason Ma, Vikash Kumar, Amy Zhang, 2022, ICLR.

Denoised MDPs: Learning World Models Better Than the World Itself

A. Torralba, S. Du, Phillip Isola, 2022, ICML.

A Survey of Zero-shot Generalisation in Deep Reinforcement Learning

Edward Grefenstette, Tim Rocktäschel, Amy Zhang, 2021, J. Artif. Intell. Res..

Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning

A. Torralba, Phillip Isola, Amy Zhang, 2023, ArXiv.

Mapping the world population one building at a time pdf

Xianming Liu, Nan Li, Hai-Anh H. Dang, 2017, ArXiv.

Imitation from Arbitrary Experience: A Dual Unification of Reinforcement and Imitation Learning Methods

Harshit S. Sikchi, Amy Zhang, S. Niekum, 2023, ArXiv.

Learning Representations for Pixel-based Control: What Matters and Why? pdf

Manan Tomar, Utkarsh A. Mishra, Amy Zhang, 2021, Trans. Mach. Learn. Res..

LIV: Language-Image Representations and Rewards for Robotic Control

Yecheng Jason Ma, Vikash Kumar, Amy Zhang, 2023, ICML.

A Model-Based Solution to the Offline Multi-Agent Reinforcement Learning Coordination Problem

Amy Zhang, Derek Nowrouzezahrai, Paul Barde, 2023, AAMAS.

Composable Planning with Attributes pdf

Rob Fergus, Arthur Szlam, Sainbayar Sukhbaatar, 2018, ICML.

Provably Efficient Offline Goal-Conditioned Reinforcement Learning with General Function Approximation and Single-Policy Concentrability

Amy Zhang, Hanlin Zhu, 2023, ArXiv.

A Low-Rank Approximation for MDPs via Moment Coupling

Amy Zhang, Itai Gurvich, 2022, Operations Research.

Provably Efficient Representation Learning in Low-rank Markov Decision Processes pdf

Quanquan Gu, Amy Zhang, Jiafan He, 2021, ArXiv.

Sequence Modeling is a Robust Contender for Offline Reinforcement Learning

Rohan Chitnis, Amy Zhang, A. Geramifard, 2023, ArXiv.

Dual RL: Unification and New Methods for Reinforcement and Imitation Learning

Harshit S. Sikchi, Amy Zhang, Qinqing Zheng, 2023, 2302.08560.

Robust Policy Learning over Multiple Uncertainty Sets

Joelle Pineau, Chelsea Finn, A. Xie, 2022, ICML.

Generalization Across Observation Shifts in Reinforcement Learning

Amy Zhang, Anuj Mahajan, 2023, arXiv.org.

Model-Invariant State Abstractions for Model-Based Reinforcement Learning

Matthew E. Taylor, Joelle Pineau, R. Calandra, 2021, ArXiv.

Improving Generalization with Approximate Factored Value Functions

S. Levine, Amy Zhang, Shagun Sodhani, 2023, Trans. Mach. Learn. Res..

Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning

A. Torralba, Phillip Isola, Amy Zhang, 2023, ICML.

Plan2Vec: Unsupervised Representation Learning by Latent Plans

Ari S. Morcos, P. Abbeel, Joelle Pineau, 2020, L4DC.

IFT 6085-Lecture 9 Stability , Generalization and the Applications of Stability

Ioannis Mitliagkas, W. Fedus, Amy Zhang, 2020 .

Provably efficient representation selection in Low-rank Markov Decision Processes: from online to offline RL

Quanquan Gu, Amy Zhang, Jiafan He, 2023, UAI.

Learning Invariant Representations for Reinforcement Learning without Reconstruction pdf

Rowan McAllister, Yarin Gal, Roberto Calandra, 2020, ICLR.

Provably efficient representation selection in Low-rank Markov Decision Processes: from online to offline RL

Quanquan Gu, Amy Zhang, Jiafan He, 2021, UAI.