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Amy Zhang
This is just a disambiguation page, and is not intended to be the bibliography of an actual person. The links to all actual bibliographies of persons of the same or a similar name can be found below. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.
Person information
Other persons with the same name
- Amy Zhang 0001 — UT Austin, TX, USA (and 2 more)
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2020 – today
- 2024
- [j4]Aditya Mohan, Amy Zhang, Marius Lindauer:
Structure in Deep Reinforcement Learning: A Survey and Open Problems. J. Artif. Intell. Res. 79: 1167-1236 (2024) - [c13]Paul Barde, Jakob Foerster, Derek Nowrouzezahrai, Amy Zhang:
A Model-Based Solution to the Offline Multi-Agent Reinforcement Learning Coordination Problem. AAMAS 2024: 141-150 - [c12]Kianna Bolante, Kevin Chen, Quan Ze Chen, Amy Zhang:
Bringing Social Computing to Secondary School Classrooms. SIGCSE (1) 2024: 123-129 - [i22]Kianna Bolante, Kevin Chen, Quan Ze Chen, Amy Zhang:
Bringing Social Computing to Secondary School Classrooms. CoRR abs/2401.09591 (2024) - [i21]Tyler Ingebrand, Amy Zhang, Ufuk Topcu:
Zero-Shot Reinforcement Learning via Function Encoders. CoRR abs/2401.17173 (2024) - [i20]Zihan Ding, Amy Zhang, Yuandong Tian, Qinqing Zheng:
Diffusion World Model. CoRR abs/2402.03570 (2024) - [i19]Alexander Levine, Peter Stone, Amy Zhang:
Multistep Inverse Is Not All You Need. CoRR abs/2403.11940 (2024) - 2023
- [j3]Robert Kirk, Amy Zhang, Edward Grefenstette, Tim Rocktäschel:
A Survey of Zero-shot Generalisation in Deep Reinforcement Learning. J. Artif. Intell. Res. 76: 201-264 (2023) - [c11]Mulong Luo, Wenjie Xiong, Geunbae Lee, Yueying Li, Xiaomeng Yang, Amy Zhang, Yuandong Tian, Hsien-Hsin S. Lee, G. Edward Suh:
AutoCAT: Reinforcement Learning for Automated Exploration of Cache-Timing Attacks. HPCA 2023: 317-332 - [c10]Tongzhou Wang, Antonio Torralba, Phillip Isola, Amy Zhang:
Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning. ICML 2023: 36411-36430 - [c9]Siddhant Agarwal, Ishan Durugkar, Peter Stone, Amy Zhang:
f-Policy Gradients: A General Framework for Goal-Conditioned RL using f-Divergences. NeurIPS 2023 - [c8]Hanlin Zhu, Amy Zhang:
Provably Efficient Offline Goal-Conditioned Reinforcement Learning with General Function Approximation and Single-Policy Concentrability. NeurIPS 2023 - [i18]Hanlin Zhu, Amy Zhang:
Provably Efficient Offline Goal-Conditioned Reinforcement Learning with General Function Approximation and Single-Policy Concentrability. CoRR abs/2302.03770 (2023) - [i17]Qiaojie Zheng, Jiucai Zhang, Amy Zhang, Xiaoli Zhang:
Confidence-aware 3D Gaze Estimation and Evaluation Metric. CoRR abs/2303.10062 (2023) - [i16]Tongzhou Wang, Antonio Torralba, Phillip Isola, Amy Zhang:
Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning. CoRR abs/2304.01203 (2023) - [i15]Shagun Jhaver, Alice Qian Zhang, Quanze Chen, Nikhila Natarajan, Ruotong Wang, Amy Zhang:
Personalizing Content Moderation on Social Media: User Perspectives on Moderation Choices, Interface Design, and Labor. CoRR abs/2305.10374 (2023) - [i14]Paul Barde, Jakob Foerster, Derek Nowrouzezahrai, Amy Zhang:
A Model-Based Solution to the Offline Multi-Agent Reinforcement Learning Coordination Problem. CoRR abs/2305.17198 (2023) - [i13]Jie Zhu, Mengsha Hu, Xueyao Liang, Amy Zhang, Ruoming Jin, Rui Liu:
Fairness-Sensitive Policy-Gradient Reinforcement Learning for Reducing Bias in Robotic Assistance. CoRR abs/2306.04167 (2023) - [i12]Anuj Mahajan, Amy Zhang:
Generalization Across Observation Shifts in Reinforcement Learning. CoRR abs/2306.04595 (2023) - [i11]Aditya Mohan, Amy Zhang, Marius Lindauer:
Structure in Reinforcement Learning: A Survey and Open Problems. CoRR abs/2306.16021 (2023) - [i10]Andre Ye, Quan Ze Chen, Amy Zhang:
Confidence Contours: Uncertainty-Aware Annotation for Medical Semantic Segmentation. CoRR abs/2308.07528 (2023) - [i9]Siddhant Agarwal, Ishan Durugkar, Peter Stone, Amy Zhang:
f-Policy Gradients: A General Framework for Goal Conditioned RL using f-Divergences. CoRR abs/2310.06794 (2023) - [i8]Rui Yang, Han Zhong, Jiawei Xu, Amy Zhang, Chongjie Zhang, Lei Han, Tong Zhang:
Towards Robust Offline Reinforcement Learning under Diverse Data Corruption. CoRR abs/2310.12955 (2023) - [i7]Rostand A. K. Fezeu, Timothy J. Salo, Amy Zhang, Zhi-Li Zhang:
Dissecting IoT Device Provisioning Process. CoRR abs/2310.14125 (2023) - [i6]Brett Barkley, Amy Zhang, David Fridovich-Keil:
An Investigation of Time Reversal Symmetry in Reinforcement Learning. CoRR abs/2311.17008 (2023) - 2022
- [c7]Amy Zhang, Aaron Brookhouse, Daniel Hammer, Francesca Spezzano, Liljana Babinkostova:
Predicting the Influence of Fake and Real News Spreaders (Student Abstract). AAAI 2022: 13107-13108 - [c6]Tongzhou Wang, Simon S. Du, Antonio Torralba, Phillip Isola, Amy Zhang, Yuandong Tian:
Denoised MDPs: Learning World Models Better Than the World Itself. ICML 2022: 22591-22612 - [i5]Tongzhou Wang, Simon S. Du, Antonio Torralba, Phillip Isola, Amy Zhang, Yuandong Tian:
Denoised MDPs: Learning World Models Better Than the World Itself. CoRR abs/2206.15477 (2022) - [i4]Mulong Luo, Wenjie Xiong, Geunbae Lee, Yueying Li, Xiaomeng Yang, Amy Zhang, Yuandong Tian, Hsien-Hsin S. Lee, G. Edward Suh:
AutoCAT: Reinforcement Learning for Automated Exploration of Cache Timing-Channel Attacks. CoRR abs/2208.08025 (2022) - [i3]Edwin Zhang, Yujie Lu, William Wang, Amy Zhang:
LAD: Language Augmented Diffusion for Reinforcement Learning. CoRR abs/2210.15629 (2022) - [i2]Chris Lengerich, Gabriel Synnaeve, Amy Zhang, Hugh Leather, Kurt Shuster, François Charton, Charysse Redwood:
Contrastive Distillation Is a Sample-Efficient Self-Supervised Loss Policy for Transfer Learning. CoRR abs/2212.11353 (2022) - 2021
- [c5]Calvin Alan Liang, Emily Tseng, Sachin R. Pendse, Crystal Lee, Kimberley R. Allison, Neilly H. Tan, Ruotong Wang, Alexandra To, Amy Zhang:
Subtle CSCW Traits: Tensions Around Identity Formation and Online Activism in the Asian Diaspora. CSCW Companion 2021: 347-351 - [i1]Robert Kirk, Amy Zhang, Edward Grefenstette, Tim Rocktäschel:
A Survey of Generalisation in Deep Reinforcement Learning. CoRR abs/2111.09794 (2021)
2010 – 2019
- 2019
- [j2]Deena M. A. Gendoo, Robert E. Denroche, Amy Zhang, Nikolina Radulovich, Gun Ho Jang, Mathieu Lemire, Sandra Fischer, Dianne Chadwick, Ilinca M. Lungu, Emin Ibrahimov, Ping-Jiang Cao, Lincoln D. Stein, Julie M. Wilson, John M. S. Bartlett, Ming-Sound Tsao, Neesha Dhani, David Hedley, Steven Gallinger, Benjamin Haibe-Kains:
Whole genomes define concordance of matched primary, xenograft, and organoid models of pancreas cancer. PLoS Comput. Biol. 15(1) (2019) - 2018
- [j1]Amelia Bateman, Oliver K. Zhao, Andrea V. Bajcsy, Mathew C. Jennings, Bryan N. Toth, Alexa J. Cohen, Emily L. Horton, Anish Khattar, Ryan S. Kuo, Felix A. Lee, Meilin K. Lim, Laura W. Migasiuk, Ramkesh Renganathan, Amy Zhang, Márcio A. Oliveira:
A user-centered design and analysis of an electrostatic haptic touchscreen system for students with visual impairments. Int. J. Hum. Comput. Stud. 109: 102-111 (2018) - 2013
- [c4]Adithya Renduchintala, Amy Zhang, Thomas Polzin, Gilan Saawadi:
Using Machine Learning and HL7 LOINC DO for Classification of Clinical Documents. AMIA 2013 - [c3]Haiyi Zhu, Amy Zhang, Jiping He, Robert E. Kraut, Aniket Kittur:
Effects of peer feedback on contribution: a field experiment in Wikipedia. CHI 2013: 2253-2262 - 2010
- [c2]Amy Zhang, Monica Cardella:
Knowledge transmission and engineering teaching. ICLS (1) 2010: 1087-1094
2000 – 2009
- 2006
- [c1]Ruchir Bindal, Pei Cao, William Chan, Jan Medved, George Suwala, Tony Bates, Amy Zhang:
Improving Traffic Locality in BitTorrent via Biased Neighbor Selection. ICDCS 2006: 66
Coauthor Index
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last updated on 2024-05-08 21:01 CEST by the dblp team
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