Jose H. Blanchet

Renyuan Xu

Zhengyuan Zhou

Math. Oper. Res., 2024

Limit Theorems for Stochastic Gradient Descent with Infinite Variance.

[BibT_eX]

[DOI]

Aleksandar Mijatovic

Wenhao Yang

CoRR, 2024

Double Distributionally Robust Bid Shading for First Price Auctions.

[BibT_eX]

[DOI]

CoRR, 2024

Optimal Downsampling for Imbalanced Classification with Generalized Linear Models.

[BibT_eX]

[DOI]

Yan Chen

Krzysztof Dembczynski

Laura Fee Nern

Aaron Flores

CoRR, 2024

Distributionally Robust Optimization as a Scalable Framework to Characterize Extreme Value Distributions.

[BibT_eX]

[DOI]

CoRR, 2024

Generative Learning for Simulation of Vehicle Faults.

[BibT_eX]

[DOI]

CoRR, 2024

ScoreFusion: fusing score-based generative models via Kullback-Leibler barycenters.

[BibT_eX]

[DOI]

CoRR, 2024

Statistical Learning of Distributionally Robust Stochastic Control in Continuous State Spaces.

[BibT_eX]

[DOI]

CoRR, 2024

Deep Learning for Computing Convergence Rates of Markov Chains.

[BibT_eX]

[DOI]

Yanlin Qu

CoRR, 2024

Provably Mitigating Overoptimization in RLHF: Your SFT Loss is Implicitly an Adversarial Regularizer.

[BibT_eX]

[DOI]

CoRR, 2024

Consistency of Neural Causal Partial Identification.

[BibT_eX]

[DOI]

Jiyuan Tan

Vasilis Syrgkanis

CoRR, 2024

Stability Evaluation via Distributional Perturbation Analysis.

[BibT_eX]

[DOI]

CoRR, 2024

Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithm.

[BibT_eX]

[DOI]

CoRR, 2024

When are Unbiased Monte Carlo Estimators More Preferable than Biased Ones?

[BibT_eX]

[DOI]

Guanyang Wang

CoRR, 2024

Automatic Outlier Rectification via Optimal Transport.

[BibT_eX]

[DOI]

CoRR, 2024

Accelerated Sampling of Rare Events using a Neural Network Bias Potential.

[BibT_eX]

[DOI]

CoRR, 2024

Orthogonal Bootstrap: Efficient Simulation of Input Uncertainty.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Single-Trajectory Distributionally Robust Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Stability Evaluation through Distributional Perturbation Analysis.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Optimal Sample Complexity for Average Reward Markov Decision Processes.

[BibT_eX]

[DOI]

Shengbo Wang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Feasible Q-Learning for Average Reward Reinforcement Learning.

[BibT_eX]

[DOI]

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

2023

Distributionally Robust Batch Contextual Bandits.

[BibT_eX]

[DOI]

Manag. Sci., October, 2023

Dropout Training is Distributionally Robust Optimal.

[BibT_eX]

[DOI]

José Luis Montiel Olea

Xuhui Zhang

J. Mach. Learn. Res., 2023

On the Foundation of Distributionally Robust Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Sample Complexity of Variance-reduced Distributionally Robust Q-learning.

[BibT_eX]

[DOI]

CoRR, 2023

When can Regression-Adjusted Control Variates Help? Rare Events, Sobolev Embedding and Minimax Optimality.

[BibT_eX]

[DOI]

CoRR, 2023

Neural Network Accelerated Process Design of Polycrystalline Microstructures.

[BibT_eX]

[DOI]

CoRR, 2023

Optimal Sample Complexity of Reinforcement Learning for Uniformly Ergodic Discounted Markov Decision Processes.

[BibT_eX]

[DOI]

Shengbo Wang

CoRR, 2023

Single-Trajectory Distributionally Robust Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Statistical Limit Theorems in Distributionally Robust Optimization.

[BibT_eX]

[DOI]

Alexander Shapiro

Proceedings of the Winter Simulation Conference, 2023

Universal Gradient Descent Ascent Method for Nonconvex-Nonconcave Minimax Optimization.

[BibT_eX]

[DOI]

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

Payoff-based Learning with Matrix Multiplicative Weights in Quantum Games.

[BibT_eX]

[DOI]

Kyriakos Lotidis

Panayotis Mertikopoulos

Nicholas Bambos

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

Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage.

[BibT_eX]

[DOI]

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

When can Regression-Adjusted Control Variate Help? Rare Events, Sobolev Embedding and Minimax Optimality.

[BibT_eX]

[DOI]

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

Dynamic Flows on Curved Space Generated by Labeled Data.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

A Convergent Single-Loop Algorithm for Relaxation of Gromov-Wasserstein in Graph Data.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Minimax Optimal Kernel Operator Learning via Multilevel Training.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

A Finite Sample Complexity Bound for Distributionally Robust Q-learning.

[BibT_eX]

[DOI]

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

Wasserstein Distributionally Robust Linear-Quadratic Estimation under Martingale Constraints.

[BibT_eX]

[DOI]

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

2022

Asymptotically Optimal Control of a Centralized Dynamic Matching Market with General Utilities.

[BibT_eX]

[DOI]

Oper. Res., November, 2022

Some open problems in exact simulation of stochastic differential equations.

[BibT_eX]

[DOI]

Queueing Syst. Theory Appl., 2022

Optimal Transport-Based Distributionally Robust Optimization: Structural Properties and Iterative Schemes.

[BibT_eX]

[DOI]

Fan Zhang

Math. Oper. Res., 2022

Distributionally Robust Mean-Variance Portfolio Selection with Wasserstein Distances.

[BibT_eX]

[DOI]

Lin Chen

Xun Yu Zhou

Manag. Sci., 2022

No Weighted-Regret Learning in Adversarial Bandits with Delays.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2022

Synthetic Principal Component Design: Fast Covariate Balancing with Synthetic Controls.

[BibT_eX]

[DOI]

CoRR, 2022

Distributionally Robust Offline Reinforcement Learning with Linear Function Approximation.

[BibT_eX]

[DOI]

CoRR, 2022

Fast and Provably Convergent Algorithms for Gromov-Wasserstein in Graph Learning.

[BibT_eX]

[DOI]

CoRR, 2022

The Design and Implementation of a Broadly Applicable Algorithm for Optimizing Intra-Day Surgical Scheduling.

[BibT_eX]

[DOI]

CoRR, 2022

Surgical Scheduling via Optimization and Machine Learning with Long-Tailed Data.

[BibT_eX]

[DOI]

CoRR, 2022

Human Imperceptible Attacks and Applications to Improve Fairness.

[BibT_eX]

[DOI]

Proceedings of the Winter Simulation Conference, 2022

Modeling extremes with d-max-decreasing neural networks.

[BibT_eX]

[DOI]

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Tikhonov Regularization is Optimal Transport Robust under Martingale Constraints.

[BibT_eX]

[DOI]

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

Sobolev Acceleration and Statistical Optimality for Learning Elliptic Equations via Gradient Descent.

[BibT_eX]

[DOI]

Yiping Lu

Lexing Ying

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

Distributionally Robust Q-Learning.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Machine Learning For Elliptic PDEs: Fast Rate Generalization Bound, Neural Scaling Law and Minimax Optimality.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

A Class of Geometric Structures in Transfer Learning: Minimax Bounds and Optimality.

[BibT_eX]

[DOI]

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

2021

Sample Out-of-Sample Inference Based on Wasserstein Distance.

[BibT_eX]

[DOI]

Oper. Res., 2021

Human Imperceptible Attacks and Applications to Improve Fairness.

[BibT_eX]

[DOI]

CoRR, 2021

Statistical Analysis of Wasserstein Distributionally Robust Estimators.

[BibT_eX]

[DOI]

Karthyek Murthy

CoRR, 2021

No Discounted-Regret Learning in Adversarial Bandits with Delays.

[BibT_eX]

[DOI]

CoRR, 2021

Deep Extreme Value Copulas for Estimation and Sampling.

[BibT_eX]

[DOI]

CoRR, 2021

Measuring Reliability of Object Detection Algorithms for Automated Driving Perception Tasks.

[BibT_eX]

[DOI]

Huanzhong Xu

Marcos Paul Gerardo-Castro

Shreyasha Paudel

Proceedings of the Winter Simulation Conference, 2021

Adversarial Regression with Doubly Non-negative Weighting Matrices.

[BibT_eX]

[DOI]

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

Modified Frank Wolfe in Probability Space.

[BibT_eX]

[DOI]

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

Sequential Domain Adaptation by Synthesizing Distributionally Robust Experts.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Testing Group Fairness via Optimal Transport Projections.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

A Statistical Test for Probabilistic Fairness.

[BibT_eX]

[DOI]

Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

Finite-Sample Regret Bound for Distributionally Robust Offline Tabular Reinforcement Learning.

[BibT_eX]

[DOI]

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

2020

Rates of Convergence to Stationarity for Reflected Brownian Motion.

[BibT_eX]

[DOI]

Xinyun Chen

Math. Oper. Res., 2020

Machine Learning's Dropout Training is Distributionally Robust Optimal.

[BibT_eX]

[DOI]

Jose Luis Montiel Olea

Xuhui Zhang

CoRR, 2020

A Distributionally Robust Approach to Fair Classification.

[BibT_eX]

[DOI]

CoRR, 2020

Distributional Robust Batch Contextual Bandits.

[BibT_eX]

[DOI]

CoRR, 2020

Sequential Batch Learning in Finite-Action Linear Contextual Bandits.

[BibT_eX]

[DOI]

CoRR, 2020

Asymptotically Optimal Control of a Centralized Dynamic Matching Market with General Utilities.

[BibT_eX]

[DOI]

CoRR, 2020

A Class of Optimal Transport Regularized Formulations with Applications to Wasserstein GANs.

[BibT_eX]

[DOI]

Saied Mahdian

Proceedings of the Winter Simulation Conference, 2020

Quantifying the Empirical Wasserstein Distance to a Set of Measures: Beating the Curse of Dimensionality.

[BibT_eX]

[DOI]

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

Distributionally Robust Parametric Maximum Likelihood Estimation.

[BibT_eX]

[DOI]

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

Distributionally Robust Local Non-parametric Conditional Estimation.

[BibT_eX]

[DOI]

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

Distributionally Robust Policy Evaluation and Learning in Offline Contextual Bandits.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Robust Bayesian Classification Using An Optimistic Score Ratio.

[BibT_eX]

[DOI]

Nian Si

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Convergence Rate Analysis of a Stochastic Trust-Region Method via Supermartingales.

[BibT_eX]

[DOI]

INFORMS J. Optim., April, 2019

Queue length asymptotics for the multiple-server queue with heavy-tailed Weibull service times.

[BibT_eX]

[DOI]

Queueing Syst. Theory Appl., 2019

Optimal uncertainty size in distributionally robust inverse covariance estimation.

[BibT_eX]

[DOI]

Nian Si

Oper. Res. Lett., 2019

Efficient Rare-Event Simulation for Multiple Jump Events in Regularly Varying Random Walks and Compound Poisson Processes.

[BibT_eX]

[DOI]

Math. Oper. Res., 2019

Quantifying Distributional Model Risk via Optimal Transport.

[BibT_eX]

[DOI]

Math. Oper. Res., 2019

Perfect Sampling of Generalized Jackson Networks.

[BibT_eX]

[DOI]

Xinyun Chen

Math. Oper. Res., 2019

Robust Wasserstein profile inference and applications to machine learning.

[BibT_eX]

[DOI]

Karthyek Rajhaa A. M.

J. Appl. Probab., 2019

Exact sampling of the infinite horizon maximum of a random walk over a nonlinear boundary.

[BibT_eX]

[DOI]

Zhipeng Liu

J. Appl. Probab., 2019

Rare-Event Simulation for Distribution Networks.

[BibT_eX]

[DOI]

Marvin K. Nakayama

Oper. Res., 2019

Optimal Transport Relaxations with Application to Wasserstein GANs.

[BibT_eX]

[DOI]

Saied Mahdian

CoRR, 2019

A Distributionally Robust Boosting Algorithm.

[BibT_eX]

[DOI]

Proceedings of the 2019 Winter Simulation Conference, 2019

Data-Driven Optimal Transport Cost Selection For Distributionally Robust Optimization.

[BibT_eX]

[DOI]

Fan Zhang

Proceedings of the 2019 Winter Simulation Conference, 2019

Learning in Generalized Linear Contextual Bandits with Stochastic Delays.

[BibT_eX]

[DOI]

Zhengyuan Zhou

Renyuan Xu

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

Semi-Parametric Dynamic Contextual Pricing.

[BibT_eX]

[DOI]

Virag Shah

Ramesh Johari

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

Multivariate Distributionally Robust Convex Regression under Absolute Error Loss.

[BibT_eX]

[DOI]

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

Online EXP3 Learning in Adversarial Bandits with Delayed Feedback.

[BibT_eX]

[DOI]

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

Probability Functional Descent: A Unifying Perspective on GANs, Variational Inference, and Reinforcement Learning.

[BibT_eX]

[DOI]

Casey Chu

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

2018

Perfect sampling of GI/GI/c queues.

[BibT_eX]

[DOI]

Yanan Pei

Queueing Syst. Theory Appl., 2018

Exact simulation of multidimensional reflected Brownian motion.

[BibT_eX]

[DOI]

Karthyek Rajhaa A. M.

J. Appl. Probab., 2018

Towards Optimal Running Times for Optimal Transport.

[BibT_eX]

[DOI]

CoRR, 2018

Bandit Learning with Positive Externalities.

[BibT_eX]

[DOI]

Virag Shah

Ramesh Johari

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

2017

Computing worst-case expectations given marginals via simulation.

[BibT_eX]

[DOI]

Fei He

Proceedings of the 2017 Winter Simulation Conference, 2017

Distributionally Robust Groupwise Regularization Estimator.

[BibT_eX]

[DOI]

Proceedings of The 9th Asian Conference on Machine Learning, 2017

2016

A Markov Chain Approximation to Choice Modeling.

[BibT_eX]

[DOI]

Guillermo Gallego

Vineet Goyal

Oper. Res., 2016

2015

Exact Sampling of Stationary and Time-Reversed Queues.

[BibT_eX]

[DOI]

Aya Wallwater

ACM Trans. Model. Comput. Simul., 2015

Tail asymptotics for delay in a half-loaded GI/GI/2 queue with heavy-tailed job sizes.

[BibT_eX]

[DOI]

Queueing Syst. Theory Appl., 2015

Affine Point Processes: Approximation and Efficient Simulation.

[BibT_eX]

[DOI]

Math. Oper. Res., 2015

Budget-constrained stochastic approximation.

[BibT_eX]

[DOI]

Uday V. Shanbhag

Proceedings of the 2015 Winter Simulation Conference, 2015

Unbiased Monte Carlo for optimization and functions of expectations via multi-level randomization.

[BibT_eX]

[DOI]

Proceedings of the 2015 Winter Simulation Conference, 2015

Unbiased monte carlo computation of smooth functions of expectations via Taylor expansions.

[BibT_eX]

[DOI]

Nan Chen

Proceedings of the 2015 Winter Simulation Conference, 2015

2014

Rare-Event Simulation for Many-Server Queues.

[BibT_eX]

[DOI]

Math. Oper. Res., 2014

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

[BibT_eX]

[DOI]

Christopher Dolan

Proceedings of the 2014 Winter Simulation Conference, 2014

2013

Rare-event simulation for stochastic recurrence equations with heavy-tailed innovations.

[BibT_eX]

[DOI]

Henrik Hult

ACM Trans. Model. Comput. Simul., 2013

Characterizing optimal sampling of binary contingency tables via the configuration model.

[BibT_eX]

[DOI]

Alexandre Stauffer

Random Struct. Algorithms, 2013

Editorial foreword to special issue on Simulation of Stochastic Networks and related topics.

[BibT_eX]

[DOI]

Gareth O. Roberts

Queueing Syst. Theory Appl., 2013

Large deviations for the empirical mean of an M/M/1 queue.

[BibT_eX]

[DOI]

Sean P. Meyn

Queueing Syst. Theory Appl., 2013

Efficient rare event simulation for heavy-tailed systems via cross entropy.

[BibT_eX]

[DOI]

Yixi Shi

Oper. Res. Lett., 2013

Asymptotics of the area under the graph of a Lévy-driven workload process.

[BibT_eX]

[DOI]

Michel Mandjes

Oper. Res. Lett., 2013

Optimal Sampling of Overflow Paths in Jackson Networks.

[BibT_eX]

[DOI]

Math. Oper. Res., 2013

Optimal rare event Monte Carlo for Markov modulated regularly varying random walks.

[BibT_eX]

[DOI]

Sandeep Juneja

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

Efficient splitting-based rare event simulation algorithms for heavy-tailed sums.

[BibT_eX]

[DOI]

Yixi Shi

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

Power line control under uncertainty of ambient temperature.

[BibT_eX]

[DOI]

Daniel Bienstock

Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

Stochastic models and control for electrical power line temperature.

[BibT_eX]

[DOI]

Daniel Bienstock

Proceedings of the 51st Annual Allerton Conference on Communication, 2013

2012

On Lyapunov Inequalities and Subsolutions for Efficient Importance Sampling.

[BibT_eX]

[DOI]

ACM Trans. Model. Comput. Simul., 2012

Rare-event simulation for multi-server queues in the Halfin-Whitt regime.

[BibT_eX]

[DOI]

SIGMETRICS Perform. Evaluation Rev., 2012

Sampling point processes on stable unbounded regions and exact simulation of queues.

[BibT_eX]

[DOI]

Proceedings of the Winter Simulation Conference, 2012

Empirical Analysis of a Stochastic Approximation Approach for Computing Quasi-stationary Distributions.

[BibT_eX]

[DOI]

Shuheng Zheng

Proceedings of the EVOLVE, 2012

2011

Efficient rare event simulation for heavy-tailed compound sums.

[BibT_eX]

[DOI]

Chenxin Li

ACM Trans. Model. Comput. Simul., 2011

Efficient simulation of tail probabilities of sums of correlated lognormals.

[BibT_eX]

[DOI]

Søren Asmussen

Sandeep Juneja

Leonardo Rojas-Nandayapa

Ann. Oper. Res., 2011

A conditional Monte Carlo method for estimating the failure probability of a distribution network with random demands.

[BibT_eX]

[DOI]

Marvin K. Nakayama

Proceedings of the Winter Simulation Conference 2011, 2011

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

[BibT_eX]

[DOI]

Proceedings of the Winter Simulation Conference 2011, 2011

Rare event simulation techniques.

[BibT_eX]

[DOI]

Proceedings of the Winter Simulation Conference 2011, 2011

Importance sampling for stochastic recurrence equations with heavy tailed increments.

[BibT_eX]

[DOI]

Henrik Hult

Proceedings of the Winter Simulation Conference 2011, 2011

2010

Asymptotic robustness of estimators in rare-event simulation.

[BibT_eX]

[DOI]

ACM Trans. Model. Comput. Simul., 2010

Asymptotic expansions of defective renewal equations with applications to perturbed risk models and processor sharing queues.

[BibT_eX]

[DOI]

Bert Zwart

Math. Methods Oper. Res., 2010

Analysis of a Splitting Estimator for Rare Event Probabilities in Jackson Networks

[BibT_eX]

[DOI]

Yixi Shi

CoRR, 2010

Monte Carlo for large credit portfolios with potentially high correlations.

[BibT_eX]

[DOI]

Xuan Yang

Proceedings of the 2010 Winter Simulation Conference, 2010

2009

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

[BibT_eX]

[DOI]

Queueing Syst. Theory Appl., 2009

Rare Event Simulation for a Generalized Hawkes Process.

[BibT_eX]

[DOI]

Proceedings of the 2009 Winter Simulation Conference, 2009

Efficient Rare Event Simulation of Continuous Time Markovian Perpetuities.

[BibT_eX]

[DOI]

Proceedings of the 2009 Winter Simulation Conference, 2009

Rare Event Simulation and Counting Problems.

[BibT_eX]

[DOI]

Daniel Rudoy

Proceedings of the Rare Event Simulation using Monte Carlo Methods, 2009

Rare Event Simulation for Queues.

[BibT_eX]

[DOI]

Michel Mandjes

Proceedings of the Rare Event Simulation using Monte Carlo Methods, 2009

2008

Large deviations perspective on ordinal optimization of heavy-tailed systems.

[BibT_eX]

[DOI]

Bert Zwart

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

Efficient tail estimation for sums of correlated lognormals.

[BibT_eX]

[DOI]

Sandeep Juneja

Leonardo Rojas-Nandayapa

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

Efficient simulation for tail probabilities of Gaussian random fields.

[BibT_eX]

[DOI]

Robert J. Adler

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

2007

Editorial: rare-event simulation for queues.

[BibT_eX]

[DOI]

Michel Mandjes

Queueing Syst. Theory Appl., 2007

Fluid heuristics, Lyapunov bounds and efficient importance sampling for a heavy-tailed G/G/1 queue.

[BibT_eX]

[DOI]

Queueing Syst. Theory Appl., 2007

Efficient suboptimal rare-event simulation.

[BibT_eX]

[DOI]

Xiaowei Zhang

Proceedings of the Winter Simulation Conference, 2007

Importance sampling of compounding processes.

[BibT_eX]

[DOI]

Bert Zwart

Proceedings of the Winter Simulation Conference, 2007

Rare-event simulation for a multidimensional random walk with t distributed increments.

[BibT_eX]

[DOI]

Proceedings of the Winter Simulation Conference, 2007

Path-sampling for state-dependent importance sampling.

[BibT_eX]

[DOI]

Proceedings of the Winter Simulation Conference, 2007

2006

Efficient simulation for large deviation probabilities of sums of heavy-tailed increments.

[BibT_eX]

[DOI]

Proceedings of the Winter Simulation Conference WSC 2006, 2006

Strongly efficient estimators for light-tailed sums.

[BibT_eX]

[DOI]

Proceedings of the 1st International Conference on Performance Evaluation Methodolgies and Tools, 2006

State-dependent importance sampling and large deviations.

[BibT_eX]

[DOI]