Henry Lam

According to our database, Henry Lam authored at least 138 papers between 2009 and 2024.

Collaborative distances:

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

2024

Burn-in selection in simulating stationary time series.

Yuanbo Li, Chu Kin Chan, Chun Yip Yau, Wai Leong Ng, Henry Lam

Comput. Stat. Data Anal., April, 2024

Overconservativeness of Variance-Based Efficiency Criteria and Probabilistic Efficiency in Rare-Event Simulation.

Yuanlu Bai, Zhiyuan Huang, Henry Lam, Ding Zhao

Manag. Sci., 2024

Uncertainty Quantification and Exploration for Reinforcement Learning.

Yi Zhu, Jing Dong, Henry Lam

Oper. Res., 2024

Efficient Learning for Clustering and Optimizing Context-Dependent Designs.

Haidong Li, Henry Lam, Yijie Peng

Oper. Res., 2024

A Shrinkage Approach to Improve Direct Bootstrap Resampling Under Input Uncertainty.

Eunhye Song, Henry Lam, Russell R. Barton

INFORMS J. Comput., 2024

LLM Embeddings Improve Test-time Adaptation to Tabular Y|X-Shifts.

Yibo Zeng, Jiashuo Liu, Henry Lam, Hongseok Namkoong

CoRR, 2024

Bayesian Bandit Algorithms with Approximate Inference in Stochastic Linear Bandits.

Ziyi Huang, Henry Lam, Haofeng Zhang

CoRR, 2024

Mallows-DPO: Fine-Tune Your LLM with Preference Dispersions.

Haoxian Chen, Hanyang Zhao, Henry Lam, David D. Yao, Wenpin Tang

CoRR, 2024

Bagging Improves Generalization Exponentially.

Huajie Qian, Donghao Ying, Henry Lam, Wotao Yin

CoRR, 2024

Learning from Sparse Offline Datasets via Conservative Density Estimation.

Zhepeng Cen, Zuxin Liu, Zitong Wang, Yihang Yao, Henry Lam, Ding Zhao

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Doubly Robust Stein-Kernelized Monte Carlo Estimator: Simultaneous Bias-Variance Reduction and Supercanonical Convergence.

Henry Lam, Haofeng Zhang

J. Mach. Learn. Res., 2023

Enhanced Balancing of Bias-Variance Tradeoff in Stochastic Estimation: A Minimax Perspective.

Henry Lam, Xinyu Zhang, Xuhui Zhang

Oper. Res., 2023

Resampling Stochastic Gradient Descent Cheaply for Efficient Uncertainty Quantification.

Henry Lam, Zitong Wang

CoRR, 2023

Pseudo-Bayesian Optimization.

Haoxian Chen, Henry Lam

CoRR, 2023

Smoothed f-Divergence Distributionally Robust Optimization: Exponential Rate Efficiency and Complexity-Free Calibration.

Zhenyuan Liu, Bart P. G. Van Parys, Henry Lam

CoRR, 2023

Optimizer's Information Criterion: Dissecting and Correcting Bias in Data-Driven Optimization.

Garud Iyengar, Henry Lam, Tianyu Wang

CoRR, 2023

Short-term Temporal Dependency Detection under Heterogeneous Event Dynamic with Hawkes Processes.

Yu Chen, Fengpei Li, Anderson Schneider, Yuriy Nevmyvaka, Asohan Amarasingham, Henry Lam

CoRR, 2023

Estimate-Then-Optimize Versus Integrated-Estimation-Optimization: A Stochastic Dominance Perspective.

Adam N. Elmachtoub, Henry Lam, Haofeng Zhang, Yunfan Zhao

CoRR, 2023

Resampling Stochastic Gradient Descent Cheaply.

Henry Lam, Zitong Wang

Proceedings of the Winter Simulation Conference, 2023

Statistical Uncertainty Quantification for Expensive Black-Box Models: Methodologies and Input Uncertainty Applications.

Henry Lam

Proceedings of the Winter Simulation Conference, 2023

Optimal Batching Under Computation Budget.

Shengyi He, Henry Lam

Proceedings of the Winter Simulation Conference, 2023

Curse of Dimensionality in Rare-Event Simulation.

Yuanlu Bai, Antonius B. Dieker, Henry Lam

Proceedings of the Winter Simulation Conference, 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

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Efficient Uncertainty Quantification and Reduction for Over-Parameterized Neural Networks.

Ziyi Huang, Henry Lam, Haofeng Zhang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Bootstrap in High Dimension with Low Computation.

Henry Lam, Zhenyuan Liu

Proceedings of the International Conference on Machine Learning, 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

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Hedging against Complexity: Distributionally Robust Optimization with Parametric Approximation.

Garud Iyengar, Henry Lam, Tianyu Wang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

General Feasibility Bounds for Sample Average Approximation via Vapnik-Chervonenkis Dimension.

Henry Lam, Fengpei Li

SIAM J. Optim., June, 2022

Rare-event Simulation for Neural Network and Random Forest Predictors.

Yuanlu Bai, Zhiyuan Huang, Henry Lam, Ding Zhao

ACM Trans. Model. Comput. Simul., 2022

Subsampling to Enhance Efficiency in Input Uncertainty Quantification.

Henry Lam, Huajie Qian

Oper. Res., 2022

A New Likelihood Ratio Method for Training Artificial Neural Networks.

Yijie Peng, Li Xiao, Bernd Heidergott, L. Jeff Hong, Henry Lam

INFORMS J. Comput., 2022

Adaptive Data Fusion for Multi-task Non-smooth Optimization.

Henry Lam, Kaizheng Wang, Yuhang Wu, Yichen Zhang

CoRR, 2022

Evaluating Aleatoric Uncertainty via Conditional Generative Models.

Ziyi Huang, Henry Lam, Haofeng Zhang

CoRR, 2022

Test Against High-Dimensional Uncertainties: Accelerated Evaluation of Autonomous Vehicles with Deep Importance Sampling.

Mansur Arief, Zhepeng Cen, Zhenyuan Liu, Zhiyuan Huang, Henry Lam, Bo Li, Ding Zhao

CoRR, 2022

Generalized Bayesian Upper Confidence Bound with Approximate Inference for Bandit Problems.

Ziyi Huang, Henry Lam, Amirhossein Meisami, Haofeng Zhang

CoRR, 2022

Cheap Bootstrap for Input Uncertainty Quantification.

Henry Lam

Proceedings of the Winter Simulation Conference, 2022

Batching on Biased Estimators.

Shengyi He, Henry Lam

Proceedings of the Winter Simulation Conference, 2022

Distributional Input Uncertainty.

Motong Chen, Zhenyuan Liu, Henry Lam

Proceedings of the Winter Simulation Conference, 2022

Rare-Event Simulation Without Variance Reduction: An Extreme Value Theory Approach.

Yuanlu Bai, Henry Lam, Sebastian Engelke

Proceedings of the Winter Simulation Conference, 2022

Importance Sampling for Rare-Event Gradient Estimation.

Yuanlu Bai, Shengyi He, Henry Lam, Guangxin Jiang, Michael C. Fu

Proceedings of the Winter Simulation Conference, 2022

Generalization Bounds with Minimal Dependency on Hypothesis Class via Distributionally Robust Optimization.

Yibo Zeng, Henry Lam

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

Certifiable Evaluation for Autonomous Vehicle Perception Systems using Deep Importance Sampling (Deep IS).

Mansur Arief, Zhepeng Cen, Zhenyuan Liu, Zhiyuan Huang, Bo Li, Henry Lam, Ding Zhao

Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022

Scalable Safety-Critical Policy Evaluation with Accelerated Rare Event Sampling.

Mengdi Xu, Peide Huang, Fengpei Li, Jiacheng Zhu, Xuewei Qi, Kentaro Oguchi, Zhiyuan Huang, Henry Lam, Ding Zhao

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

Efficient Calibration of Multi-Agent Simulation Models from Output Series with Bayesian Optimization.

Yuanlu Bai, Henry Lam, Tucker Balch, Svitlana Vyetrenko

Proceedings of the 3rd ACM International Conference on AI in Finance, 2022

2021

Minimax efficient finite-difference stochastic gradient estimators using black-box function evaluations.

Henry Lam, Haidong Li, Xuhui Zhang

Oper. Res. Lett., 2021

Learning-Based Robust Optimization: Procedures and Statistical Guarantees.

L. Jeff Hong, Zhiyuan Huang, Henry Lam

Manag. Sci., 2021

Efficient Calibration of Multi-Agent Market Simulators from Time Series with Bayesian Optimization.

Yuanlu Bai, Henry Lam, Svitlana Vyetrenko, Tucker Balch

CoRR, 2021

Quantifying Epistemic Uncertainty in Deep Learning.

Ziyi Huang, Henry Lam, Haofeng Zhang

CoRR, 2021

Complexity-Free Generalization via Distributionally Robust Optimization.

Henry Lam, Yibo Zeng

CoRR, 2021

Accelerated Policy Evaluation: Learning Adversarial Environments with Adaptive Importance Sampling.

Mengdi Xu, Peide Huang, Fengpei Li, Jiacheng Zhu, Xuewei Qi, Kentaro Oguchi, Zhiyuan Huang, Henry Lam, Ding Zhao

CoRR, 2021

Calibrating Over-Parametrized Simulation Models: A Framework via Eligibility Set.

Yuanlu Bai, Tucker Balch, Haoxian Chen, Danial Dervovic, Henry Lam, Svitlana Vyetrenko

CoRR, 2021

Short-Term Adaptive Emergency Call Volume Prediction.

Elioth Sanabria, Henry Lam, Enrique Lelo de Larrea, Jay Sethuraman, Sevin Mohammadi, Audrey Olivier, Andrew W. Smyth, Edward M. Dolan, Nicholas E. Johnson, Timothy R. Kepler, Afsan Quayyum, Kathleen S. Thomson

Proceedings of the Winter Simulation Conference, 2021

Simulating New York City Hospital Load Balancing During COVID-19.

Enrique Lelo de Larrea, Henry Lam, Elioth Sanabria, Jay Sethuraman, Sevin Mohammadi, Audrey Olivier, Andrew W. Smyth, Edward M. Dolan, Nicholas E. Johnson, Timothy R. Kepler, Afsan Quayyum, Kathleen S. Thomson

Proceedings of the Winter Simulation Conference, 2021

Neural Predictive Intervals for Simulation Metamodeling.

Henry Lam, Haofeng Zhang

Proceedings of the Winter Simulation Conference, 2021

Higher-Order Coverage Error Analysis for Batching and Sectioning.

Shengyi He, Henry Lam

Proceedings of the Winter Simulation Conference, 2021

Learning Prediction Intervals for Regression: Generalization and Calibration.

Haoxian Chen, Ziyi Huang, Henry Lam, Huajie Qian, Haofeng Zhang

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 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

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Parametric Scenario Optimization under Limited Data: A Distributionally Robust Optimization View.

Henry Lam, Fengpei Li

ACM Trans. Model. Comput. Simul., 2020

Maximum Likelihood Estimation by Monte Carlo Simulation: Toward Data-Driven Stochastic Modeling.

Yijie Peng, Michael C. Fu, Bernd Heidergott, Henry Lam

Oper. Res., 2020

Deep Probabilistic Accelerated Evaluation: A Certifiable Rare-Event Simulation Methodology for Black-Box Autonomy.

Mansur Arief, Zhiyuan Huang, Guru Koushik Senthil Kumar, Yuanlu Bai, Shengyi He, Wenhao Ding, Henry Lam, Ding Zhao

CoRR, 2020

Sample Average Approximation For Functional Decisions Under Shape Constraints.

Dashi I. Singham, Henry Lam

Proceedings of the Winter Simulation Conference, 2020

Context-Dependent Ranking and Selection under a Bayesian Framework.

Haidong Li, Henry Lam, Zhe Liang, Yijie Peng

Proceedings of the Winter Simulation Conference, 2020

Optimally Tuning Finite-Difference Estimators.

Haidong Li, Henry Lam

Proceedings of the Winter Simulation Conference, 2020

Distributionally Constrained Stochastic Gradient Estimation Using Noisy Function Evaluations.

Henry Lam, Junhui Zhang

Proceedings of the Winter Simulation Conference, 2020

Calibrating Input Parameters via Eligibility Sets.

Yuanlu Bai, Henry Lam

Proceedings of the Winter Simulation Conference, 2020

On the Error of Naive Rare-Event Monte Carlo Estimator.

Yuanlu Bai, Henry Lam

Proceedings of the Winter Simulation Conference, 2020

Robust Importance Weighting for Covariate Shift.

Fengpei Li, Henry Lam, Siddharth Prusty

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Constrained Reinforcement Learning via Policy Splitting.

Haoxian Chen, Henry Lam, Fengpei Li, Amirhossein Meisami

Proceedings of The 12th Asian Conference on Machine Learning, 2020

2019

Recovering Best Statistical Guarantees via the Empirical Divergence-Based Distributionally Robust Optimization.

Henry Lam

Oper. Res., 2019

Optimization-Based Calibration of Simulation Input Models.

Aleksandrina Goeva, Henry Lam, Huajie Qian, Bo Zhang

Oper. Res., 2019

Robust Analysis in Stochastic Simulation: Computation and Performance Guarantees.

Soumyadip Ghosh, Henry Lam

Oper. Res., 2019

Efficient Inference and Exploration for Reinforcement Learning.

Yi Zhu, Jing Dong, Henry Lam

CoRR, 2019

Assessing Modeling Variability in Autonomous Vehicle Accelerated Evaluation.

Zhiyuan Huang, Mansur Arief, Henry Lam, Ding Zhao

CoRR, 2019

From Data to Stochastic Modeling and Decision Making: What Can We Do Better?

Joost Berkhout, Bernd Heidergott, Henry Lam, Yijie Peng

Asia Pac. J. Oper. Res., 2019

Minimax Efficient Finite-Difference Gradient Estimators.

Henry Lam, Xuhui Zhang

Proceedings of the 2019 Winter Simulation Conference, 2019

On The Stability of Kernelized Control Functionals On Partial And Biased Stochastic Inputs.

Henry Lam, Haofeng Zhang

Proceedings of the 2019 Winter Simulation Conference, 2019

Validating Optimization with Uncertain Constraints.

Henry Lam, Huajie Qian

Proceedings of the 2019 Winter Simulation Conference, 2019

Random Perturbation and Bagging to Quantify Input Uncertainty.

Henry Lam, Huajie Qian

Proceedings of the 2019 Winter Simulation Conference, 2019

On The Impacts of Tail Model Uncertainty in Rare-Event Estimation.

Zhiyuan Huang, Henry Lam

Proceedings of the 2019 Winter Simulation Conference, 2019

Evaluation Uncertainty in Data-Driven Self-Driving Testing.

Zhiyuan Huang, Mansur Arief, Henry Lam, Ding Zhao

Proceedings of the 2019 IEEE Intelligent Transportation Systems Conference, 2019

2018

Accelerated Evaluation of Automated Vehicles in Car-Following Maneuvers.

Ding Zhao, Xianan Huang, Huei Peng, Henry Lam, David J. LeBlanc

IEEE Trans. Intell. Transp. Syst., 2018

Accelerated Evaluation of Automated Vehicles Using Piecewise Mixture Models.

Zhiyuan Huang, Henry Lam, David J. LeBlanc, Ding Zhao

IEEE Trans. Intell. Transp. Syst., 2018

Sensitivity to Serial Dependency of Input Processes: A Robust Approach.

Henry Lam

Manag. Sci., 2018

Robust and parallel Bayesian model selection.

Michael Minyi Zhang, Henry Lam, Lizhen Lin

Comput. Stat. Data Anal., 2018

Assessing solution Quality in stochastic Optimization via bootstrap Aggregating.

Henry Lam, Huajie Qian

Proceedings of the 2018 Winter Simulation Conference, 2018

Subsampling variance for input uncertainty Quantification.

Henry Lam, Huajie Qian

Proceedings of the 2018 Winter Simulation Conference, 2018

Sampling uncertain Constraints under parametric distributions.

Henry Lam, Fengpei Li

Proceedings of the 2018 Winter Simulation Conference, 2018

On efficiencies of stochastic Optimization Procedures under Importance Sampling.

Henry Lam, Guangxin Jiang, Michael C. Fu

Proceedings of the 2018 Winter Simulation Conference, 2018

Rare-Event simulation without Structural Information: a Learning-based Approach.

Zhiyuan Huang, Henry Lam, Ding Zhao

Proceedings of the 2018 Winter Simulation Conference, 2018

Designing Importance samplers to simulate Machine Learning Predictors via Optimization.

Zhiyuan Huang, Henry Lam, Ding Zhao

Proceedings of the 2018 Winter Simulation Conference, 2018

Constructing simulation output Intervals under input uncertainty via Data sectioning.

Peter W. Glynn, Henry Lam

Proceedings of the 2018 Winter Simulation Conference, 2018

Achieving Optimal Bias-variance Tradeoff in Online derivative estimation.

Thibault Duplay, Henry Lam, Xinyu Zhang

Proceedings of the 2018 Winter Simulation Conference, 2018

Revisiting Direct bootstrap resampling for input Model uncertainty.

Russell R. Barton, Henry Lam, Eunhye Song

Proceedings of the 2018 Winter Simulation Conference, 2018

Sequential Learning under Probabilistic Constraints.

Amirhossein Meisami, Henry Lam, Chen Dong, Abhishek Pani

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Synthesis of Different Autonomous Vehicles Test Approaches.

Zhiyuan Huang, Mansur Arief, Henry Lam, Ding Zhao

Proceedings of the 21st International Conference on Intelligent Transportation Systems, 2018

A Versatile Approach to Evaluating and Testing Automated Vehicles based on Kernel Methods.

Zhiyuan Huang, Yaohui Guo, Mansur Arief, Henry Lam, Ding Zhao

Proceedings of the 2018 Annual American Control Conference, 2018

2017

Accelerated Evaluation of Automated Vehicles Safety in Lane-Change Scenarios Based on Importance Sampling Techniques.

Ding Zhao, Henry Lam, Huei Peng, Shan Bao, David J. LeBlanc, Kazutoshi Nobukawa, Christopher S. Pan

IEEE Trans. Intell. Transp. Syst., 2017

The empirical likelihood approach to quantifying uncertainty in sample average approximation.

Henry Lam, Enlu Zhou

Oper. Res. Lett., 2017

Tail Analysis Without Parametric Models: A Worst-Case Perspective.

Henry Lam, Clementine Mottet

Oper. Res., 2017

A Versatile Approach to Evaluating and Testing Automated Vehicles based on Kernel Methods.

Zhiyuan Huang, Yaohui Guo, Henry Lam, Ding Zhao

CoRR, 2017

Uncertainty quantification on simulation analysis driven by random forests.

Amirhossein Meisami, Mark P. Van Oyen, Henry Lam

Proceedings of the 2017 Winter Simulation Conference, 2017

Improving prediction from stochastic simulation via model discrepancy learning.

Henry Lam, Xinyu Zhang, Matthew Plumlee

Proceedings of the 2017 Winter Simulation Conference, 2017

Sequential experimentation to efficiently test automated vehicles.

Zhiyuan Huang, Henry Lam, Ding Zhao

Proceedings of the 2017 Winter Simulation Conference, 2017

Computing worst-case expectations given marginals via simulation.

Jose H. Blanchet, Fei He, Henry Lam

Proceedings of the 2017 Winter Simulation Conference, 2017

An accelerated testing approach for automated vehicles with background traffic described by joint distributions.

Zhiyuan Huang, Henry Lam, Ding Zhao

Proceedings of the 20th IEEE International Conference on Intelligent Transportation Systems, 2017

Towards affordable on-track testing for autonomous vehicle - A Kriging-based statistical approach.

Zhiyuan Huang, Henry Lam, Ding Zhao

Proceedings of the 20th IEEE International Conference on Intelligent Transportation Systems, 2017

Evaluation of automated vehicles in the frontal cut-in scenario - An enhanced approach using piecewise mixture models.

Zhiyuan Huang, Ding Zhao, Henry Lam, David J. LeBlanc, Huei Peng

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

2016

Robust Sensitivity Analysis for Stochastic Systems.

Henry Lam

Math. Oper. Res., 2016

Accelerated Evaluation of Automated Vehicles based on Importance Sampling Techniques.

Ding Zhao, Henry Lam, Huei Peng, Shan Bao, David J. LeBlanc, Kazutoshi Nobukawa, Christopher S. Pan

CoRR, 2016

Accelerated Evaluation of Automated Vehicles using Piecewise Mixture Distribution Models.

Zhiyuan Huang, Ding Zhao, Henry Lam, David J. LeBlanc, Huei Peng

CoRR, 2016

Learning stochastic model discrepancy.

Matthew Plumlee, Henry Lam

Proceedings of the Winter Simulation Conference, 2016

The empirical likelihood approach to simulation input uncertainty.

Henry Lam, Huajie Qian

Proceedings of the Winter Simulation Conference, 2016

Advanced tutorial: Input uncertainty and robust analysis in stochastic simulation.

Henry Lam

Proceedings of the Winter Simulation Conference, 2016

Approximating data-driven joint chance-constrained programs via uncertainty set construction.

L. Jeff Hong, Zhiyuan Huang, Henry Lam

Proceedings of the Winter Simulation Conference, 2016

2015

A Bayesian Approach for Online Classifier Ensemble.

Qinxun Bai, Henry Lam, Stan Sclaroff

CoRR, 2015

Quantifying uncertainty in sample average approximation.

Henry Lam, Enlu Zhou

Proceedings of the 2015 Winter Simulation Conference, 2015

Simulating tail events with unspecified tail models.

Henry Lam, Clementine Mottet

Proceedings of the 2015 Winter Simulation Conference, 2015

A statistical perspective on linear programs with uncertain parameters.

L. Jeff Hong, Henry Lam

Proceedings of the 2015 Winter Simulation Conference, 2015

Mirror descent stochastic approximation for computing worst-case stochastic input models.

Soumyadip Ghosh, Henry Lam

Proceedings of the 2015 Winter Simulation Conference, 2015

2014

Learning about Social Learning in MOOCs: From Statistical Analysis to Generative Model.

Christopher G. Brinton, Mung Chiang, Shaili Jain, Henry Lam, Zhenming Liu, Felix Ming Fai Wong

IEEE Trans. Learn. Technol., 2014

Rare-Event Simulation for Many-Server Queues.

Jose H. Blanchet, Henry Lam

Math. Oper. Res., 2014

From Black-Scholes to Online Learning: Dynamic Hedging under Adversarial Environments.

Henry Lam, Zhenming Liu

CoRR, 2014

Reconstructing input models via simulation optimization.

Aleksandrina Goeva, Henry Lam, Bo Zhang

Proceedings of the 2014 Winter Simulation Conference, 2014

Robust rare-event performance analysis with natural non-convex constraints.

Jose H. Blanchet, Christopher Dolan, Henry Lam

Proceedings of the 2014 Winter Simulation Conference, 2014

A Bayesian Framework for Online Classifier Ensemble.

Qinxun Bai, Henry Lam, Stan Sclaroff

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Graph-based peak alignment algorithms for multiple liquid chromatography-mass spectrometry datasets.

Jijie Wang, Henry Lam

Bioinform., 2013

Iterative methods for robust estimation under bivariate distributional uncertainty.

Henry Lam, Soumyadip Ghosh

Proceedings of the Winter Simulations Conference: Simulation Making Decisions in a Complex World, 2013

Why Steiner-tree type algorithms work for community detection.

Mung Chiang, Henry Lam, Zhenming Liu, H. Vincent Poor

Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012

Efficient importance sampling under partial information.

Henry Lam

Proceedings of the Winter Simulation Conference, 2012

Chernoff-Hoeffding Bounds for Markov Chains: Generalized and Simplified.

Kai-Min Chung, Henry Lam, Zhenming Liu, Michael Mitzenmacher

Proceedings of the 29th International Symposium on Theoretical Aspects of Computer Science, 2012

Information dissemination via random walks in <i>d</i>-dimensional space.

Henry Lam, Zhenming Liu, Michael Mitzenmacher, Xiaorui Sun, Yajun Wang

Proceedings of the Twenty-Third Annual ACM-SIAM Symposium on Discrete Algorithms, 2012

2011

Information Dissemination via Random Walks in d-Dimensional Space

Henry Lam, Zhenming Liu, Michael Mitzenmacher, Xiaorui Sun, Yajun Wang

CoRR, 2011

Importance sampling for actuarial cost analysis under a heavy traffic model.

Jose H. Blanchet, Henry Lam

Proceedings of the Winter Simulation Conference 2011, 2011

Rare event simulation techniques.

Jose H. Blanchet, Henry Lam

Proceedings of the Winter Simulation Conference 2011, 2011

Exact asymptotic for infinite-server queues.

Henry Lam

Proceedings of the 6th International Conference on Queueing Theory and Network Applications, 2011

2010

Spectral Library Searching for Peptide Identification via Tandem MS.

Henry Lam, Ruedi Aebersold

Proceedings of the Proteome Bioinformatics, 2010

2009

Rare event simulation for a slotted time <i>M</i>/<i>G</i>/<i>s</i> model.

Jose H. Blanchet, Peter W. Glynn, Henry Lam

Queueing Syst. Theory Appl., 2009