Amy Zhang
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
43
Venues
11
Active years
2006–2025
Best venue rank
A*
Where they publish
Papers
43 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ACL | StitchLLM: Serving LLMs, One Block at a Time. | Bodun Hu, Shuozhe Li, Saurabh Agarwal, Myungjin Lee, Akshay Jajoo, Jiamin Li, Le Xu, Geon-Woo Kim, Donghyun Kim, Hong Xu, Amy Zhang, Aditya Akella |
| 2025 | ICLR | Learning a Fast Mixing Exogenous Block MDP using a Single Trajectory. | Alexander Levine, Peter Stone, Amy Zhang |
| 2025 | ICLR | Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning. | Caleb Chuck, Fan Feng, Carl Qi, Chang Shi, Siddhant Agarwal, Amy Zhang, Scott Niekum |
| 2025 | ICLR | Towards General-Purpose Model-Free Reinforcement Learning. | Scott Fujimoto, Pierluca D'Oro, Amy Zhang, Yuandong Tian, Michael Rabbat |
| 2025 | ICLR | MaestroMotif: Skill Design from Artificial Intelligence Feedback. | Martin Klissarov, Mikael Henaff, Roberta Raileanu, Shagun Sodhani, Pascal Vincent, Amy Zhang, Pierre-Luc Bacon, Doina Precup, Marlos C. Machado, Pierluca D'Oro |
| 2025 | ICLR | EC-Diffuser: Multi-Object Manipulation via Entity-Centric Behavior Generation. | Carl Qi, Dan Haramati, Tal Daniel, Aviv Tamar, Amy Zhang |
| 2025 | ICLR | An Optimal Discriminator Weighted Imitation Perspective for Reinforcement Learning. | Haoran Xu, Shuozhe Li, Harshit Sikchi, Scott Niekum, Amy Zhang |
| 2025 | ICML | Proto Successor Measure: Representing the Behavior Space of an RL Agent. | Siddhant Agarwal, Harshit Sikchi, Peter Stone, Amy Zhang |
| 2024 | CoRL | A Dual Approach to Imitation Learning from Observations with Offline Datasets. | Harshit Sikchi, Caleb Chuck, Amy Zhang, Scott Niekum |
| 2024 | ICLR | Towards Robust Offline Reinforcement Learning under Diverse Data Corruption. | Rui Yang, Han Zhong, Jiawei Xu, Amy Zhang, Chongjie Zhang, Lei Han, Tong Zhang |
| 2024 | ICLR | When should we prefer Decision Transformers for Offline Reinforcement Learning? | Prajjwal Bhargava, Rohan Chitnis, Alborz Geramifard, Shagun Sodhani, Amy Zhang |
| 2024 | ICLR | Motif: Intrinsic Motivation from Artificial Intelligence Feedback. | Martin Klissarov, Pierluca D'Oro, Shagun Sodhani, Roberta Raileanu, Pierre-Luc Bacon, Pascal Vincent, Amy Zhang, Mikael Henaff |
| 2024 | ICLR | Score Models for Offline Goal-Conditioned Reinforcement Learning. | Harshit Sikchi, Rohan Chitnis, Ahmed Touati, Alborz Geramifard, Amy Zhang, Scott Niekum |
| 2024 | ICLR | Dual RL: Unification and New Methods for Reinforcement and Imitation Learning. | Harshit Sikchi, Qinqing Zheng, Amy Zhang, Scott Niekum |
| 2024 | ICLR | Language Control Diffusion: Efficiently Scaling through Space, Time, and Tasks. | Edwin Zhang, Yujie Lu, Shinda Huang, William Yang Wang, Amy Zhang |
| 2024 | ICML | Zero-Shot Reinforcement Learning via Function Encoders. | Tyler Ingebrand, Amy Zhang, Ufuk Topcu |
| 2024 | RO-MAN | Fairness-Sensitive Policy-Gradient Reinforcement Learning for Reducing Bias in Robotic Assistance. | Jie Zhu, Mengsha Hu, Amy Zhang, Ruoming Jin, Rui Liu |
| 2023 | HPCA | AutoCAT: Reinforcement Learning for Automated Exploration of Cache-Timing Attacks. | Mulong Luo, Wenjie Xiong, Geunbae Lee, Yueying Li, Xiaomeng Yang, Amy Zhang, Yuandong Tian, Hsien-Hsin S. Lee, G. Edward Suh |
| 2023 | ICLR | Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement. | Michael Chang, Alyssa L. Dayan, Franziska Meier, Thomas L. Griffiths, Sergey Levine, Amy Zhang |
| 2023 | ICLR | VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training. | Yecheng Jason Ma, Shagun Sodhani, Dinesh Jayaraman, Osbert Bastani, Vikash Kumar, Amy Zhang |
| 2023 | ICLR | BC-IRL: Learning Generalizable Reward Functions from Demonstrations. | Andrew Szot, Amy Zhang, Dhruv Batra, Zsolt Kira, Franziska Meier |
| 2023 | ICLR | Latent State Marginalization as a Low-cost Approach for Improving Exploration. | Dinghuai Zhang, Aaron C. Courville, Yoshua Bengio, Qinqing Zheng, Amy Zhang, Ricky T. Q. Chen |
| 2023 | ICML | Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning. | Tongzhou Wang, Antonio Torralba, Phillip Isola, Amy Zhang |
| 2023 | ICML | LIV: Language-Image Representations and Rewards for Robotic Control. | Yecheng Jason Ma, Vikash Kumar, Amy Zhang, Osbert Bastani, Dinesh Jayaraman |
| 2023 | UAI | Provably efficient representation selection in Low-rank Markov Decision Processes: from online to offline RL. | Weitong Zhang, Jiafan He, Dongruo Zhou, Amy Zhang, Quanquan Gu |
| 2022 | AAAI | Predicting the Influence of Fake and Real News Spreaders (Student Abstract). | Amy Zhang, Aaron Brookhouse, Daniel Hammer, Francesca Spezzano, Liljana Babinkostova |
| 2022 | ICML | Denoised MDPs: Learning World Models Better Than the World Itself. | Tongzhou Wang, Simon S. Du, Antonio Torralba, Phillip Isola, Amy Zhang, Yuandong Tian |
| 2022 | ICML | Bisimulation Makes Analogies in Goal-Conditioned Reinforcement Learning. | Philippe Hansen-Estruch, Amy Zhang, Ashvin Nair, Patrick Yin, Sergey Levine |
| 2022 | ICML | Robust Policy Learning over Multiple Uncertainty Sets. | Annie Xie, Shagun Sodhani, Chelsea Finn, Joelle Pineau, Amy Zhang |
| 2022 | ICML | Online Decision Transformer. | Qinqing Zheng, Amy Zhang, Aditya Grover |
| 2021 | AAAI | Improving Sample Efficiency in Model-Free Reinforcement Learning from Images. | Denis Yarats, Amy Zhang, Ilya Kostrikov, Brandon Amos, Joelle Pineau, Rob Fergus |
| 2021 | ICLR | Learning Invariant Representations for Reinforcement Learning without Reconstruction. | Amy Zhang, Rowan Thomas McAllister, Roberto Calandra, Yarin Gal, Sergey Levine |
| 2021 | ICLR | Learning Robust State Abstractions for Hidden-Parameter Block MDPs. | Amy Zhang, Shagun Sodhani, Khimya Khetarpal, Joelle Pineau |
| 2021 | ICML | Out-of-Distribution Generalization via Risk Extrapolation (REx). | David Krueger, Ethan Caballero, Jrn-Henrik Jacobsen, Amy Zhang, Jonathan Binas, Dinghuai Zhang, Rmi Le Priol, Aaron C. Courville |
| 2021 | ICML | Multi-Task Reinforcement Learning with Context-based Representations. | Shagun Sodhani, Amy Zhang, Joelle Pineau |
| 2020 | ICML | Invariant Causal Prediction for Block MDPs. | Amy Zhang, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup |
| 2020 | UAI | Stable Policy Optimization via Off-Policy Divergence Regularization. | Ahmed Touati, Amy Zhang, Joelle Pineau, Pascal Vincent |
| 2018 | ICLR | Decoupling Dynamics and Reward for Transfer Learning. | Amy Zhang, Harsh Satija, Joelle Pineau |
| 2018 | ICML | Composable Planning with Attributes. | Amy Zhang, Sainbayar Sukhbaatar, Adam Lerer, Arthur Szlam, Rob Fergus |
| 2013 | AMIA | Using Machine Learning and HL7 LOINC DO for Classification of Clinical Documents. | Adithya Renduchintala, Amy Zhang, Thomas Polzin, Gilan Saawadi |
| 2013 | CHI | Effects of peer feedback on contribution: a field experiment in Wikipedia. | Haiyi Zhu, Amy Zhang, Jiping He, Robert E. Kraut, Aniket Kittur |
| 2012 | UAI | Guess Who Rated This Movie: Identifying Users Through Subspace Clustering. | Amy Zhang, Nadia Fawaz, Stratis Ioannidis, Andrea Montanari |
| 2006 | ICDCS | Improving Traffic Locality in BitTorrent via Biased Neighbor Selection. | Ruchir Bindal, Pei Cao, William Chan, Jan Medved, George Suwala, Tony Bates, Amy Zhang |