Audrey Huang

According to our database, Audrey Huang authored at least 18 papers between 2019 and 2025.

Collaborative distances:

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

2025

Is Best-of-N the Best of Them? Coverage, Scaling, and Optimality in Inference-Time Alignment.

Audrey Huang, Adam Block, Qinghua Liu, Nan Jiang, Dylan J. Foster, Akshay Krishnamurthy

CoRR, March, 2025

Computational-Statistical Tradeoffs at the Next-Token Prediction Barrier: Autoregressive and Imitation Learning under Misspecification.

Dhruv Rohatgi, Adam Block, Audrey Huang, Akshay Krishnamurthy, Dylan J. Foster

CoRR, February, 2025

Model Selection for Off-policy Evaluation: New Algorithms and Experimental Protocol.

Pai Liu, Lingfeng Zhao, Shivangi Agarwal, Jinghan Liu, Audrey Huang, Philip Amortila, Nan Jiang

CoRR, February, 2025

Correcting the Mythos of KL-Regularization: Direct Alignment without Overoptimization via Chi-Squared Preference Optimization.

Audrey Huang, Wenhao Zhan, Tengyang Xie, Jason D. Lee, Wen Sun, Akshay Krishnamurthy, Dylan J. Foster

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Self-Improvement in Language Models: The Sharpening Mechanism.

Audrey Huang, Adam Block, Dylan J. Foster, Dhruv Rohatgi, Cyril Zhang, Max Simchowitz, Jordan T. Ash, Akshay Krishnamurthy

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Computational-Statistical Tradeoffs at the Next-Token Prediction Barrier: Autoregressive and Imitation Learning under Misspecification (extended abstract).

Dhruv Rohatgi, Adam Block, Audrey Huang, Akshay Krishnamurthy, Dylan J. Foster

Proceedings of the Thirty Eighth Annual Conference on Learning Theory, 2025

2024

Non-adaptive Online Finetuning for Offline Reinforcement Learning.

Audrey Huang, Mohammad Ghavamzadeh, Nan Jiang, Marek Petrik

RLJ, 2024

Occupancy-based Policy Gradient: Estimation, Convergence, and Optimality.

Audrey Huang, Nan Jiang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Timing as an Action: Learning When to Observe and Act.

Helen Zhou, Audrey Huang, Kamyar Azizzadenesheli, David Childers, Zachary C. Lipton

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Reinforcement Learning in Low-rank MDPs with Density Features.

Audrey Huang, Jinglin Chen, Nan Jiang

Proceedings of the International Conference on Machine Learning, 2023

Extended Abstract: Learning in Low-rank MDPs with Density Features.

Audrey Huang, Jinglin Chen, Nan Jiang

Proceedings of the 57th Annual Conference on Information Sciences and Systems, 2023

2022

Beyond the Return: Off-policy Function Estimation under User-specified Error-measuring Distributions.

Audrey Huang, Nan Jiang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Supervised Learning with General Risk Functionals.

Liu Leqi, Audrey Huang, Zachary C. Lipton, Kamyar Azizzadenesheli

Proceedings of the International Conference on Machine Learning, 2022

Offline Reinforcement Learning with Realizability and Single-policy Concentrability.

Wenhao Zhan, Baihe Huang, Audrey Huang, Nan Jiang, Jason D. Lee

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Off-Policy Risk Assessment for Markov Decision Processes.

Audrey Huang, Liu Leqi, Zachary C. Lipton, Kamyar Azizzadenesheli

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

On the Convergence and Optimality of Policy Gradient for Markov Coherent Risk.

Audrey Huang, Liu Leqi, Zachary C. Lipton, Kamyar Azizzadenesheli

CoRR, 2021

Off-Policy Risk Assessment in Contextual Bandits.

Audrey Huang, Liu Leqi, Zachary C. Lipton, Kamyar Azizzadenesheli

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

2019

Graph-Structured Visual Imitation.

Maximilian Sieb, Xian Zhou, Audrey Huang, Oliver Kroemer, Katerina Fragkiadaki

Proceedings of the 3rd Annual Conference on Robot Learning, 2019