Audrey Huang - RankMe

31 papers A* 10A 2Misc 2Journal 17

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Unifying View of Coverage in Linear Off-Policy Evaluation. CoRR Philip Amortila, Audrey Huang, Akshay Krishnamurthy, Nan Jiang
2026	J	`jnl`	Learning to Reason with Curriculum I: Provable Benefits of Autocurriculum. CoRR Nived Rajaraman, Audrey Huang, Miroslav Dudík, Robert E. Schapire, Dylan J. Foster, Akshay Krishnamurthy
2025	A*	`conf`	Computational-Statistical Tradeoffs at the Next-Token Prediction Barrier: Autoregressive and Imitation Learning under Misspecification (extended abstract). COLT Dhruv Rohatgi, Adam Block, Audrey Huang, Akshay Krishnamurthy, Dylan J. Foster
2025	J	`jnl`	Computational-Statistical Tradeoffs at the Next-Token Prediction Barrier: Autoregressive and Imitation Learning under Misspecification. CoRR Dhruv Rohatgi, Adam Block, Audrey Huang, Akshay Krishnamurthy, Dylan J. Foster
2025	A*	`conf`	Correcting the Mythos of KL-Regularization: Direct Alignment without Overoptimization via Chi-Squared Preference Optimization. ICLR Audrey Huang, Wenhao Zhan, Tengyang Xie, Jason D. Lee, Wen Sun, Akshay Krishnamurthy, Dylan J. Foster
2025	A*	`conf`	Is Best-of-N the Best of Them? Coverage, Scaling, and Optimality in Inference-Time Alignment. ICML Audrey Huang, Adam Block, Qinghua Liu, Nan Jiang, Akshay Krishnamurthy, Dylan J. Foster
2025	J	`jnl`	Is Best-of-N the Best of Them? Coverage, Scaling, and Optimality in Inference-Time Alignment. CoRR Audrey Huang, Adam Block, Qinghua Liu, Nan Jiang, Dylan J. Foster, Akshay Krishnamurthy
2025	J	`jnl`	Model Selection for Off-policy Evaluation: New Algorithms and Experimental Protocol. CoRR Pai Liu, Lingfeng Zhao, Shivangi Agarwal, Jinghan Liu, Audrey Huang, Philip Amortila, Nan Jiang
2025	A*	`conf`	Self-Improvement in Language Models: The Sharpening Mechanism. ICLR Audrey Huang, Adam Block, Dylan J. Foster, Dhruv Rohatgi, Cyril Zhang, Max Simchowitz, Jordan T. Ash, Akshay Krishnamurthy
2025	J	`jnl`	The Coverage Principle: How Pre-Training Enables Post-Training. CoRR Fan Chen, Audrey Huang, Noah Golowich, Sadhika Malladi, Adam Block, Jordan T. Ash, Akshay Krishnamurthy, Dylan J. Foster
2024	J	`jnl`	Correcting the Mythos of KL-Regularization: Direct Alignment without Overoptimization via Chi-Squared Preference Optimization. CoRR Audrey Huang, Wenhao Zhan, Tengyang Xie, Jason D. Lee, Wen Sun, Akshay Krishnamurthy, Dylan J. Foster
2024	J	`jnl`	Non-adaptive Online Finetuning for Offline Reinforcement Learning. RLJ Audrey Huang, Mohammad Ghavamzadeh, Nan Jiang, Marek Petrik
2024	A*	`conf`	Occupancy-based Policy Gradient: Estimation, Convergence, and Optimality. NeurIPS Audrey Huang, Nan Jiang
2024	J	`jnl`	Self-Improvement in Language Models: The Sharpening Mechanism. CoRR Audrey Huang, Adam Block, Dylan J. Foster, Dhruv Rohatgi, Cyril Zhang, Max Simchowitz, Jordan T. Ash, Akshay Krishnamurthy
2024	A	`conf`	Timing as an Action: Learning When to Observe and Act. AISTATS Helen Zhou, Audrey Huang, Kamyar Azizzadenesheli, David Childers, Zachary C. Lipton
2023	Misc	`conf`	Extended Abstract: Learning in Low-rank MDPs with Density Features. CISS Audrey Huang, Jinglin Chen, Nan Jiang
2023	J	`jnl`	Reinforcement Learning in Low-Rank MDPs with Density Features. CoRR Audrey Huang, Jinglin Chen, Nan Jiang
2023	A*	`conf`	Reinforcement Learning in Low-rank MDPs with Density Features. ICML Audrey Huang, Jinglin Chen, Nan Jiang
2022	A*	`conf`	Beyond the Return: Off-policy Function Estimation under User-specified Error-measuring Distributions. NeurIPS Audrey Huang, Nan Jiang
2022	J	`jnl`	Beyond the Return: Off-policy Function Estimation under User-specified Error-measuring Distributions. CoRR Audrey Huang, Nan Jiang
2022	A	`conf`	Off-Policy Risk Assessment for Markov Decision Processes. AISTATS Audrey Huang, Liu Leqi, Zachary C. Lipton, Kamyar Azizzadenesheli
2022	J	`jnl`	Off-Policy Risk Assessment in Markov Decision Processes. CoRR Audrey Huang, Liu Leqi, Zachary Chase Lipton, Kamyar Azizzadenesheli
2022	A*	`conf`	Offline Reinforcement Learning with Realizability and Single-policy Concentrability. COLT Wenhao Zhan, Baihe Huang, Audrey Huang, Nan Jiang, Jason D. Lee
2022	J	`jnl`	Offline Reinforcement Learning with Realizability and Single-policy Concentrability. CoRR Wenhao Zhan, Baihe Huang, Audrey Huang, Nan Jiang, Jason D. Lee
2022	A*	`conf`	Supervised Learning with General Risk Functionals. ICML Liu Leqi, Audrey Huang, Zachary C. Lipton, Kamyar Azizzadenesheli
2022	J	`jnl`	Supervised Learning with General Risk Functionals. CoRR Liu Leqi, Audrey Huang, Zachary C. Lipton, Kamyar Azizzadenesheli
2021	A*	`conf`	Off-Policy Risk Assessment in Contextual Bandits. NeurIPS Audrey Huang, Liu Leqi, Zachary C. Lipton, Kamyar Azizzadenesheli
2021	J	`jnl`	Off-Policy Risk Assessment in Contextual Bandits. CoRR Audrey Huang, Liu Leqi, Zachary C. Lipton, Kamyar Azizzadenesheli
2021	J	`jnl`	On the Convergence and Optimality of Policy Gradient for Markov Coherent Risk. CoRR Audrey Huang, Liu Leqi, Zachary C. Lipton, Kamyar Azizzadenesheli
2019	Misc	`conf`	Graph-Structured Visual Imitation. CoRL Maximilian Sieb, Xian Zhou, Audrey Huang, Oliver Kroemer, Katerina Fragkiadaki
2019	J	`jnl`	Graph-Structured Visual Imitation. CoRR Maximilian Sieb, Xian Zhou, Audrey Huang, Oliver Kroemer, Katerina Fragkiadaki