Jose H. Blanchet

199 papers A* 30A 8C 1Misc 30Journal 123Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Deep learning for Markov chains: Lyapunov functions, Poisson's equation, and stationary distributions. Queueing Syst. Theory Appl. Yanlin Qu, Jose H. Blanchet, Peter W. Glynn
2026	J	`jnl`	Optimal Quantum Speedups for Repeatedly Nested Expectation Estimation. CoRR Yihang Sun, Guanyang Wang, Jose H. Blanchet
2026	J	`jnl`	Robust Assortment Optimization from Observational Data. CoRR Miao Lu, Yuxuan Han, Han Zhong, Zhengyuan Zhou, Jose H. Blanchet
2026	J	`jnl`	Score-based Metropolis-Hastings for Fractional Langevin Algorithms. CoRR Ahmed Aloui, Junyi Liao, Ali Hasan, Jose H. Blanchet, Vahid Tarokh
2026	J	`jnl`	Statsformer: Validated Ensemble Learning with LLM-Derived Semantic Priors. CoRR Erica Zhang, Naomi Sagan, Danny Tse, Fangzhao Zhang, Mert Pilanci, Jose H. Blanchet
2026	J	`jnl`	When Should Humans Step In? Optimal Human Dispatching in AI-Assisted Decisions. CoRR Lezhi Tan, Naomi Sagan, Lihua Lei, Jose H. Blanchet
2025	J	`jnl`	Connecting Quantum Computing with Classical Stochastic Simulation. CoRR Jose H. Blanchet, Mark S. Squillante, Mario Szegedy, Guanyang Wang
2025	J	`jnl`	Convolution Bounds on Quantile Aggregation. Oper. Res. Jose H. Blanchet, Henry Lam, Yang Liu, Ruodu Wang
2025	J	`jnl`	DRO: A Python Library for Distributionally Robust Optimization in Machine Learning. CoRR Jiashuo Liu, Tianyu Wang, Henry Lam, Hongseok Namkoong, Jose H. Blanchet
2025	J	`jnl`	Deep Learning for Markov Chains: Lyapunov Functions, Poisson's Equation, and Stationary Distributions. CoRR Yanlin Qu, Jose H. Blanchet, Peter W. Glynn
2025	A*	`conf`	Epsilon-Minimax Solutions of Statistical Decision Problems via the Hedge Algorithm. EC Andres Aradillas Fernandez, Jose H. Blanchet, José Luis Montiel Olea, Chen Qiu, Jörg Stoye, Lezhi Tan
2025	J	`jnl`	Estimation of Treatment Effects in Extreme and Unobserved Data. CoRR Jiyuan Tan, Jose H. Blanchet, Vasilis Syrgkanis
2025	J	`jnl`	Fairness-Utility Trade-off via Wasserstein Projection. CoRR Yan Chen, Zheng Tan, Jose H. Blanchet, Hanzhang Qin
2025	J	`jnl`	FutureX: An Advanced Live Benchmark for LLM Agents in Future Prediction. CoRR Zhiyuan Zeng, Jiashuo Liu, Siyuan Chen, Tianci He, Yali Liao, Jinpeng Wang, Zaiyuan Wang, Yang Yang, Lingyue Yin, Mingren Yin, Zhenwei Zhu, Tianle Cai, Zehui Chen, Jiecao Chen, Yantao Du, Xiang Gao, Jiacheng Guo, Liang Hu, Jianpeng Jiao, Xiangsheng Li, Jingkai Liu, Shuang Ni, Zhoufutu Wen, Ge Zhang, Kaiyuan Zhang, Xin Zhou, Jose H. Blanchet, Xipeng Qiu, Mengdi Wang, Wenhao Huang
2025	—	`conf`	Invariance and Concentration Properties of Gradient-based Learning in Games. CDC Kyriakos Lotidis, Panayotis Mertikopoulos, Nicholas Bambos, Jose H. Blanchet
2025	J	`jnl`	LLM-Lasso: A Robust Framework for Domain-Informed Feature Selection and Regularization. CoRR Erica Zhang, Ryunosuke Goto, Naomi Sagan, Jurik Mutter, Nick Phillips, Ash A. Alizadeh, Kangwook Lee, Jose H. Blanchet, Mert Pilanci, Robert Tibshirani
2025	J	`jnl`	Learning an Optimal Assortment Policy under Observational Data. CoRR Yuxuan Han, Han Zhong, Miao Lu, Jose H. Blanchet, Zhengyuan Zhou
2025	J	`jnl`	Multi-agent learning under uncertainty: Recurrence vs. concentration. CoRR Kyriakos Lotidis, Panayotis Mertikopoulos, Nicholas Bambos, Jose H. Blanchet
2025	J	`jnl`	Non-linear Quantum Monte Carlo. CoRR Jose H. Blanchet, Yassine Hamoudi, Mario Szegedy, Guanyang Wang
2025	A	`conf`	Optimal downsampling for Imbalanced Classification with Generalized Linear Models. AISTATS Yan Chen, Jose H. Blanchet, Krzysztof Dembczynski, Laura Fee Nern, Aaron E. Flores
2025	J	`jnl`	Robust equilibria in continuous games: From strategic to dynamic robustness. CoRR Kyriakos Lotidis, Panayotis Mertikopoulos, Nicholas Bambos, Jose H. Blanchet
2025	J	`jnl`	Robustifying Conditional Portfolio Decisions via Optimal Transport. Oper. Res. Viet Anh Nguyen, Fan Zhang, Shanshan Wang, Jose H. Blanchet, Erick Delage, Yinyu Ye
2025	J	`jnl`	Sample-Path Large Deviations for Unbounded Additive Functionals of the Reflected Random Walk. Math. Oper. Res. Mihail Bazhba, Jose H. Blanchet, Chang-Han Rhee, Bert Zwart
2025	A	`conf`	ScoreFusion: Fusing Score-based Generative Models via Kullback-Leibler Barycenters. AISTATS Hao Liu, Junze Ye, Jose H. Blanchet, Nian Si
2025	A	`conf`	Statistical Learning of Distributionally Robust Stochastic Control in Continuous State Spaces. AISTATS Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou
2025	A*	`conf`	Tightening Causal Bounds via Covariate-Aware Optimal Transport. ICML Sirui Lin, Zijun Gao, Jose H. Blanchet, Peter W. Glynn
2025	J	`jnl`	Wasserstein Distributionally Robust Regret Optimization. CoRR Lukas-Benedikt Fiechtner, Jose H. Blanchet
2024	J	`jnl`	Accelerated Sampling of Rare Events using a Neural Network Bias Potential. CoRR Xinru Hua, Rasool Ahmad, Jose H. Blanchet, Wei Cai
2024	A*	`conf`	An Efficient High-dimensional Gradient Estimator for Stochastic Differential Equations. NeurIPS Shengbo Wang, Jose H. Blanchet, Peter W. Glynn
2024	A*	`conf`	Automatic Outlier Rectification via Optimal Transport. NeurIPS Jose H. Blanchet, Jiajin Li, Markus Pelger, Greg Zanotti
2024	J	`jnl`	Automatic Outlier Rectification via Optimal Transport. CoRR Jose H. Blanchet, Jiajin Li, Markus Pelger, Greg Zanotti
2024	A*	`conf`	Consistency of Neural Causal Partial Identification. NeurIPS Jiyuan Tan, Jose H. Blanchet, Vasilis Syrgkanis
2024	J	`jnl`	Consistency of Neural Causal Partial Identification. CoRR Jiyuan Tan, Jose H. Blanchet, Vasilis Syrgkanis
2024	A*	`conf`	Deep Learning for Computing Convergence Rates of Markov Chains. NeurIPS Yanlin Qu, Jose H. Blanchet, Peter W. Glynn
2024	J	`jnl`	Deep Learning for Computing Convergence Rates of Markov Chains. CoRR Yanlin Qu, Jose H. Blanchet, Peter W. Glynn
2024	A	`conf`	Distributionally Robust Optimization as a Scalable Framework to Characterize Extreme Value Distributions. UAI Patrick K. Kuiper, Ali Hasan, Wenhao Yang, Yuting Ng, Hoda Bidkhori, Jose H. Blanchet, Vahid Tarokh
2024	J	`jnl`	Distributionally Robust Optimization as a Scalable Framework to Characterize Extreme Value Distributions. CoRR Patrick K. Kuiper, Ali Hasan, Wenhao Yang, Yuting Ng, Hoda Bidkhori, Jose H. Blanchet, Vahid Tarokh
2024	J	`jnl`	Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithm. CoRR Miao Lu, Han Zhong, Tong Zhang, Jose H. Blanchet
2024	A*	`conf`	Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithms. NeurIPS Miao Lu, Han Zhong, Tong Zhang, Jose H. Blanchet
2024	J	`jnl`	Double Distributionally Robust Bid Shading for First Price Auctions. CoRR Yanlin Qu, Ravi Kant, Yan Chen, Brendan Kitts, San Gultekin, Aaron Flores, Jose H. Blanchet
2024	A	`conf`	Feasible Q-Learning for Average Reward Reinforcement Learning. AISTATS Ying Jin, Ramki Gummadi, Zhengyuan Zhou, Jose H. Blanchet
2024	Misc	`conf`	Generative Learning for Simulation of Vehicle Faults. WSC Patrick K. Kuiper, Sirui Lin, Jose H. Blanchet, Vahid Tarokh
2024	J	`jnl`	Generative Learning for Simulation of Vehicle Faults. CoRR Patrick K. Kuiper, Sirui Lin, Jose H. Blanchet, Vahid Tarokh
2024	J	`jnl`	Limit Theorems for Stochastic Gradient Descent with Infinite Variance. CoRR Jose H. Blanchet, Aleksandar Mijatovic, Wenhao Yang
2024	J	`jnl`	Optimal Downsampling for Imbalanced Classification with Generalized Linear Models. CoRR Yan Chen, Jose H. Blanchet, Krzysztof Dembczynski, Laura Fee Nern, Aaron Flores
2024	J	`jnl`	Orthogonal Bootstrap: Efficient Simulation of Input Uncertainty. CoRR Kaizhao Liu, Jose H. Blanchet, Lexing Ying, Yiping Lu
2024	A*	`conf`	Provably Mitigating Overoptimization in RLHF: Your SFT Loss is Implicitly an Adversarial Regularizer. NeurIPS Zhihan Liu, Miao Lu, Shenao Zhang, Boyi Liu, Hongyi Guo, Yingxiang Yang, Jose H. Blanchet, Zhaoran Wang
2024	J	`jnl`	Provably Mitigating Overoptimization in RLHF: Your SFT Loss is Implicitly an Adversarial Regularizer. CoRR Zhihan Liu, Miao Lu, Shenao Zhang, Boyi Liu, Hongyi Guo, Yingxiang Yang, Jose H. Blanchet, Zhaoran Wang
2024	J	`jnl`	Sample Complexity of Variance-Reduced Distributionally Robust Q-Learning. J. Mach. Learn. Res. Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou
2024	J	`jnl`	ScoreFusion: fusing score-based generative models via Kullback-Leibler barycenters. CoRR Hao Liu, Junze Ye, Jose H. Blanchet, Nian Si
2024	J	`jnl`	Stability Evaluation via Distributional Perturbation Analysis. CoRR Jose H. Blanchet, Peng Cui, Jiajin Li, Jiashuo Liu
2024	J	`jnl`	Statistical Learning of Distributionally Robust Stochastic Control in Continuous State Spaces. CoRR Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou
2024	J	`jnl`	Towards optimal running timesfor optimal transport. Oper. Res. Lett. Jose H. Blanchet, Arun Jambulapati, Carson Kent, Aaron Sidford
2024	J	`jnl`	When are Unbiased Monte Carlo Estimators More Preferable than Biased Ones? CoRR Guanyang Wang, Jose H. Blanchet, Peter W. Glynn
2023	A*	`conf`	A Convergent Single-Loop Algorithm for Relaxation of Gromov-Wasserstein in Graph Data. ICLR Jiajin Li, Jianheng Tang, Lemin Kong, Huikang Liu, Jia Li, Anthony Man-Cho So, Jose H. Blanchet
2023	J	`jnl`	A Convergent Single-Loop Algorithm for Relaxation of Gromov-Wasserstein in Graph Data. CoRR Jiajin Li, Jianheng Tang, Lemin Kong, Huikang Liu, Jia Li, Anthony Man-Cho So, Jose H. Blanchet
2023	J	`jnl`	A Finite Sample Complexity Bound for Distributionally Robust Q-learning. CoRR Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou
2023	J	`jnl`	Distributionally Robust Batch Contextual Bandits. Manag. Sci. Nian Si, Fan Zhang, Zhengyuan Zhou, Jose H. Blanchet
2023	A*	`conf`	Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage. NeurIPS Jose H. Blanchet, Miao Lu, Tong Zhang, Han Zhong
2023	J	`jnl`	Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage. CoRR Jose H. Blanchet, Miao Lu, Tong Zhang, Han Zhong
2023	J	`jnl`	Dropout Training is Distributionally Robust Optimal. J. Mach. Learn. Res. Jose H. Blanchet, Yang Kang, José Luis Montiel Olea, Viet Anh Nguyen, Xuhui Zhang
2023	A*	`conf`	Dynamic Flows on Curved Space Generated by Labeled Data. IJCAI Xinru Hua, Truyen Nguyen, Tam Le, Jose H. Blanchet, Viet Anh Nguyen
2023	J	`jnl`	Dynamic Flows on Curved Space Generated by Labeled Data. CoRR Xinru Hua, Truyen Nguyen, Tam Le, Jose H. Blanchet, Viet Anh Nguyen
2023	J	`jnl`	On the Foundation of Distributionally Robust Reinforcement Learning. CoRR Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou
2023	J	`jnl`	Optimal Sample Complexity for Average Reward Markov Decision Processes. CoRR Shengbo Wang, Jose H. Blanchet, Peter W. Glynn
2023	J	`jnl`	Optimal Sample Complexity of Reinforcement Learning for Uniformly Ergodic Discounted Markov Decision Processes. CoRR Shengbo Wang, Jose H. Blanchet, Peter W. Glynn
2023	A*	`conf`	Payoff-based Learning with Matrix Multiplicative Weights in Quantum Games. NeurIPS Kyriakos Lotidis, Panayotis Mertikopoulos, Nicholas Bambos, Jose H. Blanchet
2023	J	`jnl`	Payoff-based learning with matrix multiplicative weights in quantum games. CoRR Kyriakos Lotidis, Panayotis Mertikopoulos, Nicholas Bambos, Jose H. Blanchet
2023	J	`jnl`	Sample Complexity of Variance-reduced Distributionally Robust Q-learning. CoRR Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou
2023	J	`jnl`	Single-Trajectory Distributionally Robust Reinforcement Learning. CoRR Zhipeng Liang, Xiaoteng Ma, Jose H. Blanchet, Jiheng Zhang, Zhengyuan Zhou
2023	Misc	`conf`	Statistical Limit Theorems in Distributionally Robust Optimization. WSC Jose H. Blanchet, Alexander Shapiro
2023	A*	`conf`	Universal Gradient Descent Ascent Method for Nonconvex-Nonconcave Minimax Optimization. NeurIPS Taoli Zheng, Linglingzhi Zhu, Anthony Man-Cho So, Jose H. Blanchet, Jiajin Li
2023	A	`conf`	Wasserstein Distributionally Robust Linear-Quadratic Estimation under Martingale Constraints. AISTATS Kyriakos Lotidis, Nicholas Bambos, Jose H. Blanchet, Jiajin Li
2023	A*	`conf`	When can Regression-Adjusted Control Variate Help? Rare Events, Sobolev Embedding and Minimax Optimality. NeurIPS Jose H. Blanchet, Haoxuan Chen, Yiping Lu, Lexing Ying
2023	J	`jnl`	When can Regression-Adjusted Control Variates Help? Rare Events, Sobolev Embedding and Minimax Optimality. CoRR Jose H. Blanchet, Haoxuan Chen, Yiping Lu, Lexing Ying
2022	J	`jnl`	A Class of Geometric Structures in Transfer Learning: Minimax Bounds and Optimality. CoRR Xuhui Zhang, Jose H. Blanchet, Soumyadip Ghosh, Mark S. Squillante
2022	J	`jnl`	Asymptotically Optimal Control of a Centralized Dynamic Matching Market with General Utilities. Oper. Res. Jose H. Blanchet, Martin I. Reiman, Virag Shah, Lawrence M. Wein, Linjia Wu
2022	J	`jnl`	Distributionally Robust Mean-Variance Portfolio Selection with Wasserstein Distances. Manag. Sci. Jose H. Blanchet, Lin Chen, Xun Yu Zhou
2022	J	`jnl`	Distributionally Robust Offline Reinforcement Learning with Linear Function Approximation. CoRR Xiaoteng Ma, Zhipeng Liang, Jose H. Blanchet, Mingwen Liu, Li Xia, Jiheng Zhang, Qianchuan Zhao, Zhengyuan Zhou
2022	A*	`conf`	Distributionally Robust Q-Learning. ICML Zijian Liu, Qinxun Bai, Jose H. Blanchet, Perry Dong, Wei Xu, Zhengqing Zhou, Zhengyuan Zhou
2022	J	`jnl`	Fast and Provably Convergent Algorithms for Gromov-Wasserstein in Graph Learning. CoRR Jiajin Li, Jianheng Tang, Lemin Kong, Huikang Liu, Jia Li, Anthony Man-Cho So, Jose H. Blanchet
2022	Misc	`conf`	Human Imperceptible Attacks and Applications to Improve Fairness. WSC Xinru Hua, Huanzhong Xu, Jose H. Blanchet, Viet Anh Nguyen
2022	A*	`conf`	Machine Learning For Elliptic PDEs: Fast Rate Generalization Bound, Neural Scaling Law and Minimax Optimality. ICLR Yiping Lu, Haoxuan Chen, Jianfeng Lu, Lexing Ying, Jose H. Blanchet
2022	J	`jnl`	Minimax Optimal Kernel Operator Learning via Multilevel Training. CoRR Jikai Jin, Yiping Lu, Jose H. Blanchet, Lexing Ying
2022	A	`conf`	Modeling extremes with d-max-decreasing neural networks. UAI Ali Hasan, Khalil Elkhalil, Yuting Ng, João M. Pereira, Sina Farsiu, Jose H. Blanchet, Vahid Tarokh
2022	J	`jnl`	Optimal Transport-Based Distributionally Robust Optimization: Structural Properties and Iterative Schemes. Math. Oper. Res. Jose H. Blanchet, Karthyek R. A. Murthy, Fan Zhang
2022	J	`jnl`	Sobolev Acceleration and Statistical Optimality for Learning Elliptic Equations via Gradient Descent. CoRR Yiping Lu, Jose H. Blanchet, Lexing Ying
2022	J	`jnl`	Some open problems in exact simulation of stochastic differential equations. Queueing Syst. Theory Appl. Jose H. Blanchet
2022	J	`jnl`	Surgical Scheduling via Optimization and Machine Learning with Long-Tailed Data. CoRR Yuan Shi, Saied Mahdian, Jose H. Blanchet, Peter W. Glynn, Andrew Young Shin, David Scheinker
2022	J	`jnl`	Synthetic Principal Component Design: Fast Covariate Balancing with Synthetic Controls. CoRR Yiping Lu, Jiajin Li, Lexing Ying, Jose H. Blanchet
2022	J	`jnl`	The Design and Implementation of a Broadly Applicable Algorithm for Optimizing Intra-Day Surgical Scheduling. CoRR Jin Xie, Teng Zhang, Jose H. Blanchet, Peter W. Glynn, Matthew Randolph, David Scheinker
2022	A*	`conf`	Tikhonov Regularization is Optimal Transport Robust under Martingale Constraints. NeurIPS Jiajin Li, Sirui Lin, Jose H. Blanchet, Viet Anh Nguyen
2022	J	`jnl`	Tikhonov Regularization is Optimal Transport Robust under Martingale Constraints. CoRR Jiajin Li, Sirui Lin, Jose H. Blanchet, Viet Anh Nguyen
2021	—	`conf`	A Statistical Test for Probabilistic Fairness. FAccT Bahar Taskesen, Jose H. Blanchet, Daniel Kuhn, Viet Anh Nguyen
2021	A*	`conf`	Adversarial Regression with Doubly Non-negative Weighting Matrices. NeurIPS Tam Le, Truyen Nguyen, Makoto Yamada, Jose H. Blanchet, Viet Anh Nguyen
2021	J	`jnl`	Adversarial Regression with Doubly Non-negative Weighting Matrices. CoRR Tam Le, Truyen Nguyen, Makoto Yamada, Jose H. Blanchet, Viet Anh Nguyen
2021	J	`jnl`	Deep Extreme Value Copulas for Estimation and Sampling. CoRR Ali Hasan, Khalil Elkhalil, João M. Pereira, Sina Farsiu, Jose H. Blanchet, Vahid Tarokh
2021	A	`conf`	Finite-Sample Regret Bound for Distributionally Robust Offline Tabular Reinforcement Learning. AISTATS Zhengqing Zhou, Qinxun Bai, Zhengyuan Zhou, Linhai Qiu, Jose H. Blanchet, Peter W. Glynn
2021	J	`jnl`	Human Imperceptible Attacks and Applications to Improve Fairness. CoRR Xinru Hua, Huanzhong Xu, Jose H. Blanchet, Viet Nguyen
2021	J	`jnl`	Machine Learning For Elliptic PDEs: Fast Rate Generalization Bound, Neural Scaling Law and Minimax Optimality. CoRR Yiping Lu, Haoxuan Chen, Jianfeng Lu, Lexing Ying, Jose H. Blanchet
2021	Misc	`conf`	Measuring Reliability of Object Detection Algorithms for Automated Driving Perception Tasks. WSC Huanzhong Xu, Jose H. Blanchet, Marcos Paul Gerardo-Castro, Shreyasha Paudel
2021	J	`jnl`	No Discounted-Regret Learning in Adversarial Bandits with Delays. CoRR Ilai Bistritz, Zhengyuan Zhou, Xi Chen, Nicholas Bambos, Jose H. Blanchet
2021	J	`jnl`	Sample Out-of-Sample Inference Based on Wasserstein Distance. Oper. Res. Jose H. Blanchet, Yang Kang
2021	A*	`conf`	Sequential Domain Adaptation by Synthesizing Distributionally Robust Experts. ICML Bahar Taskesen, Man-Chung Yue, Jose H. Blanchet, Daniel Kuhn, Viet Anh Nguyen
2021	J	`jnl`	Sequential Domain Adaptation by Synthesizing Distributionally Robust Experts. CoRR Bahar Taskesen, Man-Chung Yue, Jose H. Blanchet, Daniel Kuhn, Viet Anh Nguyen
2021	J	`jnl`	Statistical Analysis of Wasserstein Distributionally Robust Estimators. CoRR Jose H. Blanchet, Karthyek Murthy, Viet Anh Nguyen
2021	A*	`conf`	Testing Group Fairness via Optimal Transport Projections. ICML Nian Si, Karthyek Murthy, Jose H. Blanchet, Viet Anh Nguyen
2021	J	`jnl`	Testing Group Fairness via Optimal Transport Projections. CoRR Nian Si, Karthyek Murthy, Jose H. Blanchet, Viet Anh Nguyen
2020	Misc	`conf`	A Class of Optimal Transport Regularized Formulations with Applications to Wasserstein GANs. WSC Saied Mahdian, Jose H. Blanchet, Peter W. Glynn
2020	J	`jnl`	A Distributionally Robust Approach to Fair Classification. CoRR Bahar Taskesen, Viet Anh Nguyen, Daniel Kuhn, Jose H. Blanchet
2020	J	`jnl`	A Statistical Test for Probabilistic Fairness. CoRR Bahar Taskesen, Jose H. Blanchet, Daniel Kuhn, Viet Anh Nguyen
2020	J	`jnl`	Asymptotically Optimal Control of a Centralized Dynamic Matching Market with General Utilities. CoRR Jose H. Blanchet, Martin I. Reiman, Virag Shah, Lawrence M. Wein
2020	J	`jnl`	Delay-Adaptive Learning in Generalized Linear Contextual Bandits. CoRR Jose H. Blanchet, Renyuan Xu, Zhengyuan Zhou
2020	J	`jnl`	Distributional Robust Batch Contextual Bandits. CoRR Nian Si, Fan Zhang, Zhengyuan Zhou, Jose H. Blanchet
2020	A*	`conf`	Distributionally Robust Policy Evaluation and Learning in Offline Contextual Bandits. ICML Nian Si, Fan Zhang, Zhengyuan Zhou, Jose H. Blanchet
2020	J	`jnl`	Machine Learning's Dropout Training is Distributionally Robust Optimal. CoRR Jose H. Blanchet, Yang Kang, Jose Luis Montiel Olea, Viet Anh Nguyen, Xuhui Zhang
2020	A*	`conf`	Quantifying the Empirical Wasserstein Distance to a Set of Measures: Beating the Curse of Dimensionality. NeurIPS Nian Si, Jose H. Blanchet, Soumyadip Ghosh, Mark S. Squillante
2020	J	`jnl`	Rates of Convergence to Stationarity for Reflected Brownian Motion. Math. Oper. Res. Jose H. Blanchet, Xinyun Chen
2020	A*	`conf`	Robust Bayesian Classification Using An Optimistic Score Ratio. ICML Viet Anh Nguyen, Nian Si, Jose H. Blanchet
2020	J	`jnl`	Robust Bayesian Classification Using an Optimistic Score Ratio. CoRR Viet Anh Nguyen, Nian Si, Jose H. Blanchet
2020	J	`jnl`	Sequential Batch Learning in Finite-Action Linear Contextual Bandits. CoRR Yanjun Han, Zhengqing Zhou, Zhengyuan Zhou, Jose H. Blanchet, Peter W. Glynn, Yinyu Ye
2019	Misc	`conf`	A Distributionally Robust Boosting Algorithm. WSC Jose H. Blanchet, Fan Zhang, Yang Kang, Zhangyi Hu
2019	J	`jnl`	A Distributionally Robust Boosting Algorithm. CoRR Jose H. Blanchet, Yang Kang, Fan Zhang, Zhangyi Hu
2019	J	`jnl`	Convergence Rate Analysis of a Stochastic Trust-Region Method via Supermartingales. INFORMS J. Optim. Jose H. Blanchet, Coralia Cartis, Matt Menickelly, Katya Scheinberg
2019	J	`jnl`	Efficient Rare-Event Simulation for Multiple Jump Events in Regularly Varying Random Walks and Compound Poisson Processes. Math. Oper. Res. Bohan Chen, Jose H. Blanchet, Chang-Han Rhee, Bert Zwart
2019	J	`jnl`	Exact sampling of the infinite horizon maximum of a random walk over a nonlinear boundary. J. Appl. Probab. Jose H. Blanchet, Jing Dong, Zhipeng Liu
2019	A*	`conf`	Learning in Generalized Linear Contextual Bandits with Stochastic Delays. NeurIPS Zhengyuan Zhou, Renyuan Xu, Jose H. Blanchet
2019	A*	`conf`	Multivariate Distributionally Robust Convex Regression under Absolute Error Loss. NeurIPS Jose H. Blanchet, Peter W. Glynn, Jun Yan, Zhengqing Zhou
2019	A*	`conf`	Online EXP3 Learning in Adversarial Bandits with Delayed Feedback. NeurIPS Ilai Bistritz, Zhengyuan Zhou, Xi Chen, Nicholas Bambos, Jose H. Blanchet
2019	J	`jnl`	Optimal Transport Relaxations with Application to Wasserstein GANs. CoRR Saied Mahdian, Jose H. Blanchet, Peter W. Glynn
2019	J	`jnl`	Optimal uncertainty size in distributionally robust inverse covariance estimation. Oper. Res. Lett. Jose H. Blanchet, Nian Si
2019	J	`jnl`	Perfect Sampling of Generalized Jackson Networks. Math. Oper. Res. Jose H. Blanchet, Xinyun Chen
2019	A*	`conf`	Probability Functional Descent: A Unifying Perspective on GANs, Variational Inference, and Reinforcement Learning. ICML Casey Chu, Jose H. Blanchet, Peter W. Glynn
2019	J	`jnl`	Probability Functional Descent: A Unifying Perspective on GANs, Variational Inference, and Reinforcement Learning. CoRR Casey Chu, Jose H. Blanchet, Peter W. Glynn
2019	J	`jnl`	Quantifying Distributional Model Risk via Optimal Transport. Math. Oper. Res. Jose H. Blanchet, Karthyek R. A. Murthy
2019	J	`jnl`	Queue length asymptotics for the multiple-server queue with heavy-tailed Weibull service times. Queueing Syst. Theory Appl. Mihail Bazhba, Jose H. Blanchet, Chang-Han Rhee, Bert Zwart
2019	J	`jnl`	Rare-Event Simulation for Distribution Networks. Oper. Res. Jose H. Blanchet, Juan Li, Marvin K. Nakayama
2019	J	`jnl`	Robust Wasserstein profile inference and applications to machine learning. J. Appl. Probab. Jose H. Blanchet, Yang Kang, Karthyek Rajhaa A. M.
2019	A*	`conf`	Semi-Parametric Dynamic Contextual Pricing. NeurIPS Virag Shah, Ramesh Johari, Jose H. Blanchet
2019	J	`jnl`	Semi-parametric dynamic contextual pricing. CoRR Virag Shah, Jose H. Blanchet, Ramesh Johari
2018	A*	`conf`	Bandit Learning with Positive Externalities. NeurIPS Virag Shah, Jose H. Blanchet, Ramesh Johari
2018	J	`jnl`	Bandit Learning with Positive Externalities. CoRR Virag Shah, Jose H. Blanchet, Ramesh Johari
2018	J	`jnl`	Exact simulation of multidimensional reflected Brownian motion. J. Appl. Probab. Jose H. Blanchet, Karthyek Rajhaa A. M.
2018	J	`jnl`	Perfect sampling of GI/GI/c queues. Queueing Syst. Theory Appl. Jose H. Blanchet, Jing Dong, Yanan Pei
2018	J	`jnl`	Towards Optimal Running Times for Optimal Transport. CoRR Jose H. Blanchet, Arun Jambulapati, Carson Kent, Aaron Sidford
2017	Misc	`conf`	Computing worst-case expectations given marginals via simulation. WSC Jose H. Blanchet, Fei He, Henry Lam
2017	C	`conf`	Distributionally Robust Groupwise Regularization Estimator. ACML Jose H. Blanchet, Yang Kang
2016	J	`jnl`	A Markov Chain Approximation to Choice Modeling. Oper. Res. Jose H. Blanchet, Guillermo Gallego, Vineet Goyal
2015	J	`jnl`	Affine Point Processes: Approximation and Efficient Simulation. Math. Oper. Res. Xiaowei Zhang, Jose H. Blanchet, Kay Giesecke, Peter W. Glynn
2015	Misc	`conf`	Budget-constrained stochastic approximation. WSC Uday V. Shanbhag, Jose H. Blanchet
2015	J	`jnl`	Exact Sampling of Stationary and Time-Reversed Queues. ACM Trans. Model. Comput. Simul. Jose H. Blanchet, Aya Wallwater
2015	J	`jnl`	Tail asymptotics for delay in a half-loaded GI/GI/2 queue with heavy-tailed job sizes. Queueing Syst. Theory Appl. Jose H. Blanchet, Karthyek R. A. Murthy
2015	Misc	`conf`	Unbiased Monte Carlo for optimization and functions of expectations via multi-level randomization. WSC Jose H. Blanchet, Peter W. Glynn
2015	Misc	`conf`	Unbiased monte carlo computation of smooth functions of expectations via Taylor expansions. WSC Jose H. Blanchet, Nan Chen, Peter W. Glynn
2014	J	`jnl`	Rare-Event Simulation for Many-Server Queues. Math. Oper. Res. Jose H. Blanchet, Henry Lam
2014	Misc	`conf`	Robust rare-event performance analysis with natural non-convex constraints. WSC Jose H. Blanchet, Christopher Dolan, Henry Lam
2013	A*	`conf`	A markov chain approximation to choice modeling. EC Jose H. Blanchet, Guillermo Gallego, Vineet Goyal
2013	J	`jnl`	Asymptotics of the area under the graph of a Lévy-driven workload process. Oper. Res. Lett. Jose H. Blanchet, Michel Mandjes
2013	J	`jnl`	Characterizing optimal sampling of binary contingency tables via the configuration model. Random Struct. Algorithms Jose H. Blanchet, Alexandre Stauffer
2013	J	`jnl`	Editorial foreword to special issue on Simulation of Stochastic Networks and related topics. Queueing Syst. Theory Appl. Jose H. Blanchet, Gareth O. Roberts
2013	J	`jnl`	Efficient rare event simulation for heavy-tailed systems via cross entropy. Oper. Res. Lett. Jose H. Blanchet, Yixi Shi
2013	Misc	`conf`	Efficient splitting-based rare event simulation algorithms for heavy-tailed sums. WSC Jose H. Blanchet, Yixi Shi
2013	J	`jnl`	Large deviations for the empirical mean of an M/M/1 queue. Queueing Syst. Theory Appl. Jose H. Blanchet, Peter W. Glynn, Sean P. Meyn
2013	J	`jnl`	Optimal Sampling of Overflow Paths in Jackson Networks. Math. Oper. Res. Jose H. Blanchet
2013	Misc	`conf`	Optimal rare event Monte Carlo for Markov modulated regularly varying random walks. WSC Karthyek R. A. Murthy, Sandeep Juneja, Jose H. Blanchet
2013	—	`conf`	Power line control under uncertainty of ambient temperature. CDC Jose H. Blanchet, Daniel Bienstock, Juan Li
2013	J	`jnl`	Rare-event simulation for stochastic recurrence equations with heavy-tailed innovations. ACM Trans. Model. Comput. Simul. Jose H. Blanchet, Henrik Hult, Kevin Leder
2013	—	`conf`	Stochastic models and control for electrical power line temperature. Allerton Daniel Bienstock, Jose H. Blanchet, Juan Li
2012	—	`conf`	Empirical Analysis of a Stochastic Approximation Approach for Computing Quasi-stationary Distributions. EVOLVE Jose H. Blanchet, Peter W. Glynn, Shuheng Zheng
2012	J	`jnl`	On Lyapunov Inequalities and Subsolutions for Efficient Importance Sampling. ACM Trans. Model. Comput. Simul. Jose H. Blanchet, Peter W. Glynn, Kevin Leder
2012	J	`jnl`	Rare-event simulation for multi-server queues in the Halfin-Whitt regime. SIGMETRICS Perform. Evaluation Rev. Jose H. Blanchet, Jing Dong
2012	Misc	`conf`	Sampling point processes on stable unbounded regions and exact simulation of queues. WSC Jose H. Blanchet, Jing Dong
2011	Misc	`conf`	A conditional Monte Carlo method for estimating the failure probability of a distribution network with random demands. WSC Jose H. Blanchet, Juan Li, Marvin K. Nakayama
2011	J	`jnl`	Efficient rare event simulation for heavy-tailed compound sums. ACM Trans. Model. Comput. Simul. Jose H. Blanchet, Chenxin Li
2011	Misc	`conf`	Efficient rare event simulation for heavy-tailed systems via cross entropy. WSC Jose H. Blanchet, Yixi Shi
2011	J	`jnl`	Efficient simulation of tail probabilities of sums of correlated lognormals. Ann. Oper. Res. Søren Asmussen, Jose H. Blanchet, Sandeep Juneja, Leonardo Rojas-Nandayapa
2011	Misc	`conf`	Importance sampling for actuarial cost analysis under a heavy traffic model. WSC Jose H. Blanchet, Henry Lam
2011	Misc	`conf`	Importance sampling for stochastic recurrence equations with heavy tailed increments. WSC Jose H. Blanchet, Henrik Hult, Kevin Leder
2011	Misc	`conf`	Rare event simulation techniques. WSC Jose H. Blanchet, Henry Lam
2010	J	`jnl`	Analysis of a Splitting Estimator for Rare Event Probabilities in Jackson Networks CoRR Jose H. Blanchet, Kevin Leder, Yixi Shi
2010	J	`jnl`	Asymptotic expansions of defective renewal equations with applications to perturbed risk models and processor sharing queues. Math. Methods Oper. Res. Jose H. Blanchet, Bert Zwart
2010	J	`jnl`	Asymptotic robustness of estimators in rare-event simulation. ACM Trans. Model. Comput. Simul. Pierre L'Ecuyer, Jose H. Blanchet, Bruno Tuffin, Peter W. Glynn
2010	J	`jnl`	Characterizing Optimal Sampling of Binary Contingency Tables via the Configuration Model CoRR Jose H. Blanchet, Alexandre Stauffer
2010	Misc	`conf`	Monte Carlo for large credit portfolios with potentially high correlations. WSC Jose H. Blanchet, Jingchen Liu, Xuan Yang
2009	Misc	`conf`	Efficient Rare Event Simulation of Continuous Time Markovian Perpetuities. WSC Jose H. Blanchet, Peter W. Glynn
2009	Misc	`conf`	Rare Event Simulation for a Generalized Hawkes Process. WSC Xiaowei Zhang, Peter W. Glynn, Kay Giesecke, Jose H. Blanchet
2009	J	`jnl`	Rare event simulation for a slotted time Queueing Syst. Theory Appl. Jose H. Blanchet, Peter W. Glynn, Henry Lam
2008	Misc	`conf`	Efficient simulation for tail probabilities of Gaussian random fields. WSC Robert J. Adler, Jose H. Blanchet, Jingchen Liu
2008	Misc	`conf`	Efficient tail estimation for sums of correlated lognormals. WSC Jose H. Blanchet, Sandeep Juneja, Leonardo Rojas-Nandayapa
2008	Misc	`conf`	Large deviations perspective on ordinal optimization of heavy-tailed systems. WSC Jose H. Blanchet, Jingchen Liu, Bert Zwart
2007	J	`jnl`	Editorial: rare-event simulation for queues. Queueing Syst. Theory Appl. Jose H. Blanchet, Michel Mandjes
2007	Misc	`conf`	Efficient suboptimal rare-event simulation. WSC Xiaowei Zhang, Jose H. Blanchet, Peter W. Glynn
2007	J	`jnl`	Fluid heuristics, Lyapunov bounds and efficient importance sampling for a heavy-tailed G/G/1 queue. Queueing Syst. Theory Appl. Jose H. Blanchet, Peter W. Glynn, Jingchen Liu
2007	Misc	`conf`	Importance sampling of compounding processes. WSC Jose H. Blanchet, Bert Zwart
2007	Misc	`conf`	Path-sampling for state-dependent importance sampling. WSC Jose H. Blanchet, Jingchen Liu
2007	Misc	`conf`	Rare-event simulation for a multidimensional random walk with WSC Jose H. Blanchet, Jingchen Liu
2006	Misc	`conf`	Efficient simulation for large deviation probabilities of sums of heavy-tailed increments. WSC Jose H. Blanchet, Jingchen Liu
2006	—	`conf`	State-dependent importance sampling and large deviations. VALUETOOLS Jose H. Blanchet, Jingchen Liu, Peter W. Glynn
2006	—	`conf`	Strongly efficient estimators for light-tailed sums. VALUETOOLS Jose H. Blanchet, Peter W. Glynn