Lookahead Optimizer: k steps forward, 1 step back. - Michael R. Zhang; James Lucas; Jimmy Ba; Geoffrey E. Hinton (NeurIPS, 2019)

Objective Social Choice: Using Auxiliary Information to Improve Voting Outcomes. - Silviu Pitis; Michael R. Zhang (AAMAS, 2020)

Benchmarks for Deep Off-Policy Evaluation. - Justin Fu; Mohammad Norouzi 002; Ofir Nachum; George Tucker; Ziyu Wang 001; Alexander Novikov 001; Mengjiao Yang 001; Michael R. Zhang; Yutian Chen 001; Aviral Kumar; Cosmin Paduraru; Sergey Levine; et al. (ICLR, 2021)

Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization. - Michael R. Zhang; Thomas Paine; Ofir Nachum; Cosmin Paduraru; George Tucker; Ziyu Wang 001; Mohammad Norouzi 002 (ICLR, 2021)

On Monotonic Linear Interpolation of Neural Network Parameters. - James Lucas; Juhan Bae; Michael R. Zhang; Stanislav Fort; Richard S. Zemel; Roger B. Grosse (ICML, 2021)

Learning Domain Invariant Representations in Goal-conditioned Block MDPs. - Beining Han; Chongyi Zheng; Harris Chan; Keiran Paster; Michael R. Zhang; Jimmy Ba (NeurIPS, 2021)

Analyzing Monotonic Linear Interpolation in Neural Network Loss Landscapes. - James Lucas; Juhan Bae; Michael R. Zhang; Stanislav Fort; Richard S. Zemel; Roger B. Grosse (CoRR, 2021)

Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization. - Michael R. Zhang; Tom Le Paine; Ofir Nachum; Cosmin Paduraru; George Tucker; Ziyu Wang 001; Mohammad Norouzi 002 (CoRR, 2021)

Decomposed Prompting to Answer Questions on a Course Discussion Board. - Brandon Jaipersaud; Paul Zhang; Jimmy Ba; Andrew Petersen 001; Lisa Zhang; Michael R. Zhang (AIED (Posters/Late Breaking Results/...), 2023)

Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve. - Juhan Bae; Michael R. Zhang; Michael Ruan; Eric Wang; So Hasegawa; Jimmy Ba; Roger Baker Grosse (ICLR, 2023)

Classifying Course Discussion Board Questions using LLMs. - Paul Zhang; Brandon Jaipersaud; Jimmy Ba; Andrew Petersen 001; Lisa Zhang; Michael R. Zhang (ITiCSE (2), 2023)

Boosted Prompt Ensembles for Large Language Models. - Silviu Pitis; Michael R. Zhang; Andrew Wang; Jimmy Ba (CoRR, 2023)

Using Large Language Models for Hyperparameter Optimization. - Michael R. Zhang; Nishkrit Desai; Juhan Bae; Jonathan Lorraine; Jimmy Ba (CoRR, 2023)

Unlearnable Algorithms for In-context Learning. - Andrei Ioan Muresanu; Anvith Thudi; Michael R. Zhang; Nicolas Papernot (CoRR, 2024)

BEADs: Bias Evaluation Across Domains. - Shaina Raza; Mizanur Rahman; Michael R. Zhang (CoRR, 2024)

Report Cards: Qualitative Evaluation of Language Models Using Natural Language Summaries. - Blair Yang; Fuyang Cui; Keiran Paster; Jimmy Ba; Pashootan Vaezipoor; Silviu Pitis; Michael R. Zhang (CoRR, 2024)