Michael R. Zhang

According to our database, Michael R. Zhang authored at least 16 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

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

BEADs: Bias Evaluation Across Domains.

Shaina Raza, Mizanur Rahman, Michael R. Zhang

CoRR, 2024

Unlearnable Algorithms for In-context Learning.

Andrei Ioan Muresanu, Anvith Thudi, Michael R. Zhang, Nicolas Papernot

CoRR, 2024

2023

Using Large Language Models for Hyperparameter Optimization.

Michael R. Zhang, Nishkrit Desai, Juhan Bae, Jonathan Lorraine, Jimmy Ba

CoRR, 2023

Boosted Prompt Ensembles for Large Language Models.

Silviu Pitis, Michael R. Zhang, Andrew Wang, Jimmy Ba

CoRR, 2023

Classifying Course Discussion Board Questions using LLMs.

Paul Zhang, Brandon Jaipersaud, Jimmy Ba, Andrew Petersen, Lisa Zhang, Michael R. Zhang

Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 2, 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

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Decomposed Prompting to Answer Questions on a Course Discussion Board.

Brandon Jaipersaud, Paul Zhang, Jimmy Ba, Andrew Petersen, Lisa Zhang, Michael R. Zhang

Proceedings of the Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky, 2023

2021

Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization.

Michael R. Zhang, Tom Le Paine, Ofir Nachum, Cosmin Paduraru, George Tucker, Ziyu Wang, Mohammad Norouzi

CoRR, 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

Learning Domain Invariant Representations in Goal-conditioned Block MDPs.

Beining Han, Chongyi Zheng, Harris Chan, Keiran Paster, Michael R. Zhang, Jimmy Ba

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On Monotonic Linear Interpolation of Neural Network Parameters.

James Lucas, Juhan Bae, Michael R. Zhang, Stanislav Fort, Richard S. Zemel, Roger B. Grosse

Proceedings of the 38th International Conference on Machine Learning, 2021

Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization.

Michael R. Zhang, Thomas Paine, Ofir Nachum, Cosmin Paduraru, George Tucker, Ziyu Wang, Mohammad Norouzi

Proceedings of the 9th International Conference on Learning Representations, 2021

Benchmarks for Deep Off-Policy Evaluation.

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

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Objective Social Choice: Using Auxiliary Information to Improve Voting Outcomes.

Silviu Pitis, Michael R. Zhang

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019

Lookahead Optimizer: k steps forward, 1 step back.

Michael R. Zhang, James Lucas, Jimmy Ba, Geoffrey E. Hinton

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019