Michael R. Zhang

23 papers A* 7A 1Journal 13Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Fast Exact Unlearning for In-Context Learning Data for LLMs. ICML Andrei Ioan Muresanu, Anvith Thudi, Michael R. Zhang, Nicolas Papernot
2024	J	`jnl`	BEADs: Bias Evaluation Across Domains. CoRR Shaina Raza, Mizanur Rahman, Michael R. Zhang
2024	J	`jnl`	Decomposed Prompting to Answer Questions on a Course Discussion Board. CoRR Brandon Jaipersaud, Paul Zhang, Jimmy Ba, Andrew Petersen, Lisa Zhang, Michael R. Zhang
2024	J	`jnl`	Report Cards: Qualitative Evaluation of Language Models Using Natural Language Summaries. CoRR Blair Yang, Fuyang Cui, Keiran Paster, Jimmy Ba, Pashootan Vaezipoor, Silviu Pitis, Michael R. Zhang
2024	J	`jnl`	Unlearnable Algorithms for In-context Learning. CoRR Andrei Ioan Muresanu, Anvith Thudi, Michael R. Zhang, Nicolas Papernot
2023	J	`jnl`	Boosted Prompt Ensembles for Large Language Models. CoRR Silviu Pitis, Michael R. Zhang, Andrew Wang, Jimmy Ba
2023	—	`conf`	Classifying Course Discussion Board Questions using LLMs. ITiCSE (2) Paul Zhang, Brandon Jaipersaud, Jimmy Ba, Andrew Petersen, Lisa Zhang, Michael R. Zhang
2023	—	`conf`	Decomposed Prompting to Answer Questions on a Course Discussion Board. AIED (Posters/Late Breaking Results/...) Brandon Jaipersaud, Paul Zhang, Jimmy Ba, Andrew Petersen, Lisa Zhang, Michael R. Zhang
2023	A*	`conf`	Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve. ICLR Juhan Bae, Michael R. Zhang, Michael Ruan, Eric Wang, So Hasegawa, Jimmy Ba, Roger Baker Grosse
2023	J	`jnl`	Using Large Language Models for Hyperparameter Optimization. CoRR Michael R. Zhang, Nishkrit Desai, Juhan Bae, Jonathan Lorraine, Jimmy Ba
2022	J	`jnl`	Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve. CoRR Juhan Bae, Michael R. Zhang, Michael Ruan, Eric Wang, So Hasegawa, Jimmy Ba, Roger B. Grosse
2021	J	`jnl`	Analyzing Monotonic Linear Interpolation in Neural Network Loss Landscapes. CoRR James Lucas, Juhan Bae, Michael R. Zhang, Stanislav Fort, Richard S. Zemel, Roger B. Grosse
2021	A*	`conf`	Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization. ICLR Michael R. Zhang, Thomas Paine, Ofir Nachum, Cosmin Paduraru, George Tucker, Ziyu Wang, Mohammad Norouzi
2021	J	`jnl`	Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization. CoRR Michael R. Zhang, Tom Le Paine, Ofir Nachum, Cosmin Paduraru, George Tucker, Ziyu Wang, Mohammad Norouzi
2021	A*	`conf`	Benchmarks for Deep Off-Policy Evaluation. ICLR 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
2021	J	`jnl`	Benchmarks for Deep Off-Policy Evaluation. CoRR 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
2021	A*	`conf`	Learning Domain Invariant Representations in Goal-conditioned Block MDPs. NeurIPS Beining Han, Chongyi Zheng, Harris Chan, Keiran Paster, Michael R. Zhang, Jimmy Ba
2021	J	`jnl`	Learning Domain Invariant Representations in Goal-conditioned Block MDPs. CoRR Beining Han, Chongyi Zheng, Harris Chan, Keiran Paster, Michael R. Zhang, Jimmy Ba
2021	A*	`conf`	On Monotonic Linear Interpolation of Neural Network Parameters. ICML James Lucas, Juhan Bae, Michael R. Zhang, Stanislav Fort, Richard S. Zemel, Roger B. Grosse
2020	A	`conf`	Objective Social Choice: Using Auxiliary Information to Improve Voting Outcomes. AAMAS Silviu Pitis, Michael R. Zhang
2020	J	`jnl`	Objective Social Choice: Using Auxiliary Information to Improve Voting Outcomes. CoRR Silviu Pitis, Michael R. Zhang
2019	A*	`conf`	Lookahead Optimizer: k steps forward, 1 step back. NeurIPS Michael R. Zhang, James Lucas, Jimmy Ba, Geoffrey E. Hinton
2019	J	`jnl`	Lookahead Optimizer: k steps forward, 1 step back. CoRR Michael R. Zhang, James Lucas, Geoffrey E. Hinton, Jimmy Ba