Michael R. Zhang

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 21

Top Topics

Linear Interpolation

Auxiliary Information

Top Venues

Publications

Shaina Raza, Mizanur Rahman, Michael R. Zhang
BEADs: Bias Evaluation Across Domains. CoRR (2024)
Andrei Muresanu, Anvith Thudi, Michael R. Zhang, Nicolas Papernot
Unlearnable Algorithms for In-context Learning. CoRR (2024)
Brandon Jaipersaud, Paul Zhang, Jimmy Ba, Andrew Petersen, Lisa Zhang, Michael R. Zhang
Decomposed Prompting to Answer Questions on a Course Discussion Board. CoRR (2024)
Paul Zhang, Brandon Jaipersaud, Jimmy Ba, Andrew Petersen, Lisa Zhang, Michael R. Zhang
Classifying Course Discussion Board Questions using LLMs. ITiCSE (2) (2023)
Michael R. Zhang, Nishkrit Desai, Juhan Bae, Jonathan Lorraine, Jimmy Ba
Using Large Language Models for Hyperparameter Optimization. CoRR (2023)
Silviu Pitis, Michael R. Zhang, Andrew Wang, Jimmy Ba
Boosted Prompt Ensembles for Large Language Models. CoRR (2023)
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)
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)
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 (2022)
Beining Han, Chongyi Zheng, Harris Chan, Keiran Paster, Michael R. Zhang, Jimmy Ba
Learning Domain Invariant Representations in Goal-conditioned Block MDPs. CoRR (2021)
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 (2021)
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)
Beining Han, Chongyi Zheng, Harris Chan, Keiran Paster, Michael R. Zhang, Jimmy Ba
Learning Domain Invariant Representations in Goal-conditioned Block MDPs. NeurIPS (2021)
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, Thomas Paine
Benchmarks for Deep Off-Policy Evaluation. ICLR (2021)
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)
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 (2021)
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 (2021)
Silviu Pitis, Michael R. Zhang
Objective Social Choice: Using Auxiliary Information to Improve Voting Outcomes. CoRR (2020)
Silviu Pitis, Michael R. Zhang
Objective Social Choice: Using Auxiliary Information to Improve Voting Outcomes. AAMAS (2020)
Michael R. Zhang, James Lucas, Geoffrey E. Hinton, Jimmy Ba
Lookahead Optimizer: k steps forward, 1 step back. CoRR (2019)
Michael R. Zhang, James Lucas, Jimmy Ba, Geoffrey E. Hinton
Lookahead Optimizer: k steps forward, 1 step back. NeurIPS (2019)