Enlu Zhou

Fumin Zhang

IEEE Trans. Autom. Control., September, 2024

Contextual Ranking and Selection with Gaussian Processes and Optimal Computing Budget Allocation.

[BibT_eX]

[DOI]

ACM Trans. Model. Comput. Simul., April, 2024

Bayesian Stochastic Gradient Descent for Stochastic Optimization with Streaming Input Data.

[BibT_eX]

[DOI]

SIAM J. Optim., March, 2024

Data-Driven Ranking and Selection Under Input Uncertainty.

[BibT_eX]

[DOI]

Oper. Res., 2024

Reusing Historical Trajectories in Natural Policy Gradient via Importance Sampling: Convergence and Convergence Rate.

[BibT_eX]

[DOI]

CoRR, 2024

Data-driven Simulation Optimization in the Age of Digital Twins.

[BibT_eX]

[DOI]

Proceedings of the 38th ACM SIGSIM Conference on Principles of Advanced Discrete Simulation, 2024

2023

Bayesian Distributionally Robust Optimization.

[BibT_eX]

[DOI]

Alexander Shapiro

SIAM J. Optim., June, 2023

Asymptotically Optimal Sampling Policy for Selecting Top-<i>m</i> Alternatives.

[BibT_eX]

[DOI]

INFORMS J. Comput., 2023

Approximate Bilevel Difference Convex Programming for Bayesian Risk Markov Decision Processes.

[BibT_eX]

[DOI]

CoRR, 2023

Input Data Collection Versus Simulation: Simultaneous Resource Allocation.

[BibT_eX]

[DOI]

Proceedings of the Winter Simulation Conference, 2023

Reusing Historical Observations in Natural Policy Gradient.

[BibT_eX]

[DOI]

Proceedings of the Winter Simulation Conference, 2023

Bayesian Risk-Averse Q-Learning with Streaming Observations.

[BibT_eX]

[DOI]

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

Cognition Difference-Based Dynamic Trust Network for Distributed Bayesian Data Fusion.

[BibT_eX]

[DOI]

IROS, 2023

Integrated Task and Motion Planning for Process-aware Source Seeking.

[BibT_eX]

[DOI]

Proceedings of the American Control Conference, 2023

2022

Bayesian Learning Model Predictive Control for Process-Aware Source Seeking.

[BibT_eX]

[DOI]

IEEE Control. Syst. Lett., 2022

Risk-averse Contextual Multi-armed Bandit Problem with Linear Payoffs.

[BibT_eX]

[DOI]

CoRR, 2022

Fixed Budget Ranking and Selection with Streaming Input Data.

[BibT_eX]

[DOI]

Proceedings of the Winter Simulation Conference, 2022

Bayesian Risk Markov Decision Processes.

[BibT_eX]

[DOI]

Yuxuan Ren

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

Robust Multi-Objective Bayesian Optimization Under Input Noise.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Risk-Aware Model Predictive Control Enabled by Bayesian Learning.

[BibT_eX]

[DOI]

Proceedings of the American Control Conference, 2022

Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably.

[BibT_eX]

[DOI]

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

2021

Solving Bayesian risk optimization via nested stochastic gradient estimation.

[BibT_eX]

[DOI]

Sait Cakmak

IISE Trans., 2021

A Bayesian Risk Approach to MDPs with Parameter Uncertainty.

[BibT_eX]

[DOI]

Yuxuan Ren

CoRR, 2021

Dynamic Sampling Policy For Subset Selection.

[BibT_eX]

[DOI]

Proceedings of the Winter Simulation Conference, 2021

A Bayesian Approach to Online Simulation Optimization with Streaming Input Data.

[BibT_eX]

[DOI]

Proceedings of the Winter Simulation Conference, 2021

Contextual Ranking and Selection with Gaussian Processes.

[BibT_eX]

[DOI]

Sait Cakmak

Siyang Gao

Proceedings of the Winter Simulation Conference, 2021

Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization.

[BibT_eX]

[DOI]

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

2020

Risk Quantification in Stochastic Simulation under Input Uncertainty.

[BibT_eX]

[DOI]

ACM Trans. Model. Comput. Simul., 2020

Domination Measure: A New Metric for Solving Multiobjective Optimization.

[BibT_eX]

[DOI]

INFORMS J. Comput., 2020

Simulation Optimization by Reusing Past Replications: Don't Be Afraid of Dependence.

[BibT_eX]

[DOI]

Proceedings of the Winter Simulation Conference, 2020

A Nested Simulation Optimization Approach for Portfolio Selection.

[BibT_eX]

[DOI]

Aly Megahed

Proceedings of the Winter Simulation Conference, 2020

Bayesian Optimization of Risk Measures.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Towards Understanding the Importance of Noise in Training Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2019

Fixed Confidence Ranking and Selection Under Input Uncertainty.

[BibT_eX]

[DOI]

Proceedings of the 2019 Winter Simulation Conference, 2019

Towards Understanding the Importance of Shortcut Connections in Residual Networks.

[BibT_eX]

[DOI]

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

Toward Understanding the Importance of Noise in Training Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Solving the Dual Problems of Dynamic Programs via Regression.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2018

Weakly Coupled Dynamic Program: Information and Lagrangian Relaxations.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2018

A Bayesian Risk Approach to Data-driven Stochastic Optimization: Formulations and Asymptotics.

[BibT_eX]

[DOI]

SIAM J. Optim., 2018

Experimental design and model reduction in systems biology.

[BibT_eX]

[DOI]

Quant. Biol., 2018

Simulation optimization of risk measures with adaptive risk levels.

[BibT_eX]

[DOI]

J. Glob. Optim., 2018

Gradient-Based Adaptive Stochastic Search for Simulation Optimization Over Continuous Space.

[BibT_eX]

[DOI]

Shalabh Bhatnagar

INFORMS J. Comput., 2018

Analyzing and provably improving fixed budget ranking and selection algorithms.

[BibT_eX]

[DOI]

CoRR, 2018

Toward Deeper Understanding of Nonconvex Stochastic Optimization with Momentum using Diffusion Approximations.

[BibT_eX]

[DOI]

CoRR, 2018

Online Quantification of input uncertainty for parametric Models.

[BibT_eX]

[DOI]

Proceedings of the 2018 Winter Simulation Conference, 2018

Provably Improving the Optimal Computing Budget Allocation Algorithm.

[BibT_eX]

[DOI]

Proceedings of the 2018 Winter Simulation Conference, 2018

Towards Understanding Acceleration Tradeoff between Momentum and Asynchrony in Nonconvex Stochastic Optimization.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

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

[BibT_eX]

[DOI]

Henry Lam

Oper. Res. Lett., 2017

A Lagrangian search method for the P-median problem.

[BibT_eX]

[DOI]

Jiming Peng

J. Glob. Optim., 2017

Robust ranking and selection with optimal computing budget allocation.

[BibT_eX]

[DOI]

Autom., 2017

Ranking and selection under input uncertainty: A budget allocation formulation.

[BibT_eX]

[DOI]

Proceedings of the 2017 Winter Simulation Conference, 2017

2016

Optimizing Conditional Value-at-Risk via gradient-based adaptive stochastic search.

[BibT_eX]

[DOI]

Proceedings of the Winter Simulation Conference, 2016

Preface.

[BibT_eX]

[DOI]

Proceedings of the Winter Simulation Conference, 2016

Optimal computing budget allocation with input uncertainty.

[BibT_eX]

[DOI]

Proceedings of the Winter Simulation Conference, 2016

2015

Information Relaxation and Dual Formulation of Controlled Markov Diffusions.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2015

Population model-based optimization.

[BibT_eX]

[DOI]

J. Glob. Optim., 2015

Estimation of conditional value-at-risk for input uncertainty with budget allocation.

[BibT_eX]

[DOI]

Proceedings of the 2015 Winter Simulation Conference, 2015

Simulation optimization when facing input uncertainty.

[BibT_eX]

[DOI]

Wei Xie

Proceedings of the 2015 Winter Simulation Conference, 2015

A sequential experiment design for input uncertainty quantification in stochastic simulation.

[BibT_eX]

[DOI]

Yuan Yi

Wei Xie

Proceedings of the 2015 Winter Simulation Conference, 2015

Quantifying uncertainty in sample average approximation.

[BibT_eX]

[DOI]

Henry Lam

Proceedings of the 2015 Winter Simulation Conference, 2015

A model-based approach to multi-objective optimization.

[BibT_eX]

[DOI]

Proceedings of the 2015 Winter Simulation Conference, 2015

2014

Model-Based Annealing Random Search with Stochastic Averaging.

[BibT_eX]

[DOI]

Jiaqiao Hu

Qi Fan

ACM Trans. Model. Comput. Simul., 2014

Gradient-Based Adaptive Stochastic Search for Non-Differentiable Optimization.

[BibT_eX]

[DOI]

Jiaqiao Hu

IEEE Trans. Autom. Control., 2014

Particle Filtering Framework for a Class of Randomized Optimization Algorithms.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2014

Simulation optimization via gradient-based stochastic search.

[BibT_eX]

[DOI]

Shalabh Bhatnagar

Proceedings of the 2014 Winter Simulation Conference, 2014

An iterative algorithm for sampling from manifolds.

[BibT_eX]

[DOI]

Chang-han Rhee

Peng Qiu

Proceedings of the 2014 Winter Simulation Conference, 2014

2013

Optimal Stopping Under Partial Observation: Near-Value Iteration.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2013

Optimal Stopping of Partially Observable Markov Processes: A Filtering-Based Duality Approach.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2013

Sequential Monte Carlo simulated annealing.

[BibT_eX]

[DOI]

J. Glob. Optim., 2013

True martingales for upper bounds on Bermudan option prices under jump-diffusion processes.

[BibT_eX]

[DOI]

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

Population model-based optimization with sequential Monte Carlo.

[BibT_eX]

[DOI]

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

2012

Efficient Selection of a Set of Good Enough Designs With Complexity Preference.

[BibT_eX]

[DOI]

Shen Yan

Chun-Hung Chen

IEEE Trans Autom. Sci. Eng., 2012

Combining gradient-based optimization with stochastic search.

[BibT_eX]

[DOI]

Jiaqiao Hu

Proceedings of the Winter Simulation Conference, 2012

Parameterized penalties in the dual representation of Markov decision processes.

[BibT_eX]

[DOI]

Proceedings of the 51th IEEE Conference on Decision and Control, 2012

2011

Pricing American options under partial observation of stochastic volatility.

[BibT_eX]

[DOI]

Proceedings of the Winter Simulation Conference 2011, 2011

2010

Solving Continuous-State POMDPs via Density Projection.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2010

A new population-based simulated annealing algorithm.

[BibT_eX]

[DOI]

Proceedings of the 2010 Winter Simulation Conference, 2010

Efficient simulation budget allocation for selecting the best set of simplest good enough designs.

[BibT_eX]

[DOI]

Shen Yan

Chun-Hung Chen

Proceedings of the 2010 Winter Simulation Conference, 2010

Simulation method for solving hybrid influence diagrams in decision making.

[BibT_eX]

[DOI]

Proceedings of the 2010 Winter Simulation Conference, 2010

2009

Particle Filtering for Stochastic Control and Global Optimization.

[BibT_eX]

[DOI]

PhD thesis, 2009

A Numerical Method for Financial Decision Problems under Stochastic Volatility.

[BibT_eX]

[DOI]

Proceedings of the 2009 Winter Simulation Conference, 2009

2008

A particle filtering framework for randomized optimization algorithms.

[BibT_eX]

[DOI]

Proceedings of the 2008 Winter Simulation Conference, Global Gateway to Discovery, 2008

A density projection approach to dimension reduction for continuous-state POMDPs.

[BibT_eX]

[DOI]