Lam, Henry

25 publications

AISTATS 2025 Dissecting the Impact of Model Misspecification in Data-Driven Optimization Adam N. Elmachtoub, Henry Lam, Haixiang Lan, Haofeng Zhang

ICLR 2025 MallowsPO: Fine-Tune Your LLM with Preference Dispersions Haoxian Chen, Hanyang Zhao, Henry Lam, David Yao, Wenpin Tang

NeurIPS 2025 Subsampled Ensemble Can Improve Generalization Tail Exponentially Huajie Qian, Donghao Ying, Henry Lam, Wotao Yin

NeurIPS 2025 The Bias-Variance Tradeoff in Data-Driven Optimization: A Local Misspecification Perspective Haixiang Lan, Luofeng Liao, Adam N. Elmachtoub, Christian Kroer, Henry Lam, Haofeng Zhang

NeurIPS 2024 Is Cross-Validation the Gold Standard to Estimate Out-of-Sample Model Performance? Garud Iyengar, Henry Lam, Tianyu Wang

NeurIPSW 2024 LLM Embeddings Improve Test-Time Adaptation to Tabular $Y|X$-Shifts Yibo Zeng, Jiashuo Liu, Henry Lam, Hongseok Namkoong

ICLR 2024 Learning from Sparse Offline Datasets via Conservative Density Estimation Zhepeng Cen, Zuxin Liu, Zitong Wang, Yihang Yao, Henry Lam, Ding Zhao

NeurIPSW 2024 Mallows-DPO: Fine-Tune Your LLM with Preference Dispersions Haoxian Chen, Hanyang Zhao, Henry Lam, David Yao, Wenpin Tang

ICML 2023 Bootstrap in High Dimension with Low Computation Henry Lam, Zhenyuan Liu

UAI 2023 Detection of Short-Term Temporal Dependencies in Hawkes Processes with Heterogeneous Background Dynamics Yu Chen, Fengpei Li, Anderson Schneider, Yuriy Nevmyvaka, Asohan Amarasingham, Henry Lam

JMLR 2023 Doubly Robust Stein-Kernelized Monte Carlo Estimator: Simultaneous Bias-Variance Reduction and Supercanonical Convergence Henry Lam, Haofeng Zhang

NeurIPS 2023 Efficient Uncertainty Quantification and Reduction for Over-Parameterized Neural Networks Ziyi Huang, Henry Lam, Haofeng Zhang

AISTATS 2023 Group Distributionally Robust Reinforcement Learning with Hierarchical Latent Variables Mengdi Xu, Peide Huang, Yaru Niu, Visak Kumar, Jielin Qiu, Chao Fang, Kuan-Hui Lee, Xuewei Qi, Henry Lam, Bo Li, Ding Zhao

AISTATS 2023 Hedging Against Complexity: Distributionally Robust Optimization with Parametric Approximation Garud Iyengar, Henry Lam, Tianyu Wang

ICMLW 2023 Learning from Sparse Offline Datasets via Conservative Density Estimation Zhepeng Cen, Zuxin Liu, Zitong Wang, Yihang Yao, Henry Lam, Ding Zhao

NeurIPS 2023 Optimal Regret Is Achievable with Bounded Approximate Inference Error: An Enhanced Bayesian Upper Confidence Bound Framework Ziyi Huang, Henry Lam, Amirhossein Meisami, Haofeng Zhang

NeurIPS 2022 Generalization Bounds with Minimal Dependency on Hypothesis Class via Distributionally Robust Optimization Yibo Zeng, Henry Lam

AISTATS 2021 Deep Probabilistic Accelerated Evaluation: A Robust Certifiable Rare-Event Simulation Methodology for Black-Box Safety-Critical Systems Mansur Arief, Zhiyuan Huang, Guru Koushik Senthil Kumar, Yuanlu Bai, Shengyi He, Wenhao Ding, Henry Lam, Ding Zhao

AISTATS 2021 Learning Prediction Intervals for Regression: Generalization and Calibration Haoxian Chen, Ziyi Huang, Henry Lam, Huajie Qian, Haofeng Zhang

ACML 2020 Constrained Reinforcement Learning via Policy Splitting Haoxian Chen, Henry Lam, Fengpei Li, Amirhossein Meisami

ICLR 2020 Efficient Inference and Exploration for Reinforcement Learning Yi Zhu, Jing Dong, Henry Lam

AISTATS 2020 Robust Importance Weighting for Covariate Shift Fengpei Li, Henry Lam, Siddharth Prusty

UAI 2018 Sequential Learning Under Probabilistic Constraints Amirhossein Meisami, Henry Lam, Chen Dong, Abhishek Pani

ICML 2014 A Bayesian Framework for Online Classifier Ensemble Qinxun Bai, Henry Lam, Stan Sclaroff

AISTATS 2013 Why Steiner-Tree Type Algorithms Work for Community Detection Mung Chiang, Henry Lam, Zhenming Liu, H. Vincent Poor