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Michael R. Zhang
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2020 – today
- 2024
- [i12]Andrei Ioan Muresanu, Anvith Thudi, Michael R. Zhang, Nicolas Papernot:
Unlearnable Algorithms for In-context Learning. CoRR abs/2402.00751 (2024) - [i11]Shaina Raza, Mizanur Rahman, Michael R. Zhang:
BEADs: Bias Evaluation Across Domains. CoRR abs/2406.04220 (2024) - [i10]Brandon Jaipersaud, Paul Zhang, Jimmy Ba, Andrew Petersen, Lisa Zhang, Michael R. Zhang:
Decomposed Prompting to Answer Questions on a Course Discussion Board. CoRR abs/2407.21170 (2024) - 2023
- [c9]Brandon Jaipersaud
, Paul Zhang
, Jimmy Ba
, Andrew Petersen
, Lisa Zhang
, Michael R. Zhang
:
Decomposed Prompting to Answer Questions on a Course Discussion Board. AIED (Posters/Late Breaking Results/...) 2023: 218-223 - [c8]Juhan Bae, Michael R. Zhang, Michael Ruan, Eric Wang, So Hasegawa, Jimmy Ba, Roger Baker Grosse:
Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve. ICLR 2023 - [c7]Paul Zhang
, Brandon Jaipersaud
, Jimmy Ba
, Andrew Petersen
, Lisa Zhang
, Michael R. Zhang
:
Classifying Course Discussion Board Questions using LLMs. ITiCSE (2) 2023: 658 - [i9]Silviu Pitis, Michael R. Zhang, Andrew Wang, Jimmy Ba:
Boosted Prompt Ensembles for Large Language Models. CoRR abs/2304.05970 (2023) - [i8]Michael R. Zhang, Nishkrit Desai, Juhan Bae, Jonathan Lorraine, Jimmy Ba:
Using Large Language Models for Hyperparameter Optimization. CoRR abs/2312.04528 (2023) - 2022
- [i7]Juhan Bae, Michael R. Zhang, Michael Ruan, Eric Wang, So Hasegawa, Jimmy Ba, Roger B. Grosse:
Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve. CoRR abs/2212.03905 (2022) - 2021
- [c6]Justin Fu, Mohammad Norouzi, Ofir Nachum, George Tucker, Ziyu Wang, Alexander Novikov, Mengjiao Yang, Michael R. Zhang, Yutian Chen, Aviral Kumar, Cosmin Paduraru, Sergey Levine, Tom Le Paine:
Benchmarks for Deep Off-Policy Evaluation. ICLR 2021 - [c5]Michael R. Zhang, Thomas Paine, Ofir Nachum, Cosmin Paduraru, George Tucker, Ziyu Wang, Mohammad Norouzi:
Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization. ICLR 2021 - [c4]James Lucas, Juhan Bae, Michael R. Zhang, Stanislav Fort, Richard S. Zemel, Roger B. Grosse:
On Monotonic Linear Interpolation of Neural Network Parameters. ICML 2021: 7168-7179 - [c3]Beining Han, Chongyi Zheng, Harris Chan, Keiran Paster, Michael R. Zhang, Jimmy Ba:
Learning Domain Invariant Representations in Goal-conditioned Block MDPs. NeurIPS 2021: 764-776 - [i6]Justin Fu, Mohammad Norouzi, Ofir Nachum, George Tucker, Ziyu Wang, Alexander Novikov, Mengjiao Yang, Michael R. Zhang, Yutian Chen, Aviral Kumar, Cosmin Paduraru, Sergey Levine, Tom Le Paine:
Benchmarks for Deep Off-Policy Evaluation. CoRR abs/2103.16596 (2021) - [i5]James Lucas, Juhan Bae, Michael R. Zhang, Stanislav Fort, Richard S. Zemel, Roger B. Grosse:
Analyzing Monotonic Linear Interpolation in Neural Network Loss Landscapes. CoRR abs/2104.11044 (2021) - [i4]Michael R. Zhang, Tom Le Paine, Ofir Nachum, Cosmin Paduraru, George Tucker, Ziyu Wang, Mohammad Norouzi:
Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization. CoRR abs/2104.13877 (2021) - [i3]Beining Han, Chongyi Zheng, Harris Chan, Keiran Paster, Michael R. Zhang, Jimmy Ba:
Learning Domain Invariant Representations in Goal-conditioned Block MDPs. CoRR abs/2110.14248 (2021) - 2020
- [c2]Silviu Pitis, Michael R. Zhang:
Objective Social Choice: Using Auxiliary Information to Improve Voting Outcomes. AAMAS 2020: 1064-1071 - [i2]Silviu Pitis, Michael R. Zhang:
Objective Social Choice: Using Auxiliary Information to Improve Voting Outcomes. CoRR abs/2001.10092 (2020)
2010 – 2019
- 2019
- [c1]Michael R. Zhang, James Lucas, Jimmy Ba, Geoffrey E. Hinton:
Lookahead Optimizer: k steps forward, 1 step back. NeurIPS 2019: 9593-9604 - [i1]Michael R. Zhang, James Lucas, Geoffrey E. Hinton, Jimmy Ba:
Lookahead Optimizer: k steps forward, 1 step back. CoRR abs/1907.08610 (2019)
Coauthor Index
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last updated on 2024-08-22 19:45 CEST by the dblp team
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