William B. Haskell

According to our database, William B. Haskell authored at least 51 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of three.

2024

An Inexact Primal-Dual Smoothing Framework for Large-Scale Non-Bilinear Saddle Point Problems.

Le Thi Khanh Hien, Renbo Zhao, William B. Haskell

J. Optim. Theory Appl., January, 2024

Correction to: The CoMirror algorithm with random constraint sampling for convex semi-infinite programming.

Bo Wei, William B. Haskell, Sixiang Zhao

Ann. Oper. Res., January, 2024

2022

Preference Robust Optimization for Choice Functions on the Space of CDFs.

William B. Haskell, Huifu Xu, Wenjie Huang

SIAM J. Optim., June, 2022

Risk Aware Minimum Principle for Optimal Control of Stochastic Differential Equations.

Jukka Isohätälä, William B. Haskell

IEEE Trans. Autom. Control., 2022

A Unifying Framework for Variance-Reduced Algorithms for Findings Zeroes of Monotone operators.

Xun Zhang, William B. Haskell, Zhisheng Ye

J. Mach. Learn. Res., 2022

A Multilevel Simulation Optimization Approach for Quantile Functions.

Songhao Wang, Szu Hui Ng, William Benjamin Haskell

INFORMS J. Comput., 2022

Learning to Price Supply Chain Contracts against a Learning Retailer.

Xuejun Zhao, Ruihao Zhu, William B. Haskell

CoRR, 2022

Robustness to Modeling Errors in Risk-Sensitive Markov Decision Problems with Markov Risk Measures.

Shiping Shao, Abhishek Gupta, William B. Haskell

CoRR, 2022

2021

Stochastic Approximation for Risk-Aware Markov Decision Processes.

Wenjie Huang, William B. Haskell

IEEE Trans. Autom. Control., 2021

Convergence of Recursive Stochastic Algorithms Using Wasserstein Divergence.

Abhishek Gupta, William B. Haskell

SIAM J. Math. Data Sci., 2021

2020

A Universal Empirical Dynamic Programming Algorithm for Continuous State MDPs.

William B. Haskell, Rahul Jain, Hiteshi Sharma, Pengqian Yu

IEEE Trans. Autom. Control., 2020

An inexact primal-dual algorithm for semi-infinite programming.

Bo Wei, William B. Haskell, Sixiang Zhao

Math. Methods Oper. Res., 2020

The CoMirror algorithm with random constraint sampling for convex semi-infinite programming.

Bo Wei, William B. Haskell, Sixiang Zhao

Ann. Oper. Res., 2020

Model and Reinforcement Learning for Markov Games with Risk Preferences.

Wenjie Huang, Pham Viet Hai, William Benjamin Haskell

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

A Unifying Framework for Variance Reduction Algorithms for Finding Zeroes of Monotone Operators.

Xun Zhang, William B. Haskell, Zhisheng Ye

CoRR, 2019

Model and Algorithm for Time-Consistent Risk-Aware Markov Games.

Wenjie Huang, Pham Viet Hai, William Benjamin Haskell

CoRR, 2019

Empirical Algorithms for General Stochastic Systems with Continuous States and Actions.

Hiteshi Sharma, Rahul Jain, William B. Haskell

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

An Optimal Algorithm for Stochastic Three-Composite Optimization.

Renbo Zhao, William B. Haskell, Vincent Y. F. Tan

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Stochastic L-BFGS: Improved Convergence Rates and Practical Acceleration Strategies.

Renbo Zhao, William B. Haskell, Vincent Y. F. Tan

IEEE Trans. Signal Process., 2018

Approximate Value Iteration for Risk-Aware Markov Decision Processes.

Pengqian Yu, William B. Haskell, Huan Xu

IEEE Trans. Autom. Control., 2018

Modeling Stochastic Dominance as Infinite-Dimensional Constraint Systems via the Strassen Theorem.

William B. Haskell, Alejandro Toriello

J. Optim. Theory Appl., 2018

Preference Elicitation and Robust Optimization with Multi-Attribute Quasi-Concave Choice Functions.

William Benjamin Haskell, Wenjie Huang, Huifu Xu

CoRR, 2018

Distributionally Robust Optimization for Sequential Decision Making.

Zhi Chen, Pengqian Yu, William B. Haskell

CoRR, 2018

Quantile simulation Optimization with stochastic Co-Kriging Model.

Songhao Wang, Szu Hui Ng, William Benjamin Haskell

Proceedings of the 2018 Winter Simulation Conference, 2018

2017

Primal-Dual Algorithms for Optimization with Stochastic Dominance.

William B. Haskell, J. George Shanthikumar, Zuo-Jun Max Shen

SIAM J. Optim., 2017

A Unified Framework for Stochastic Matrix Factorization via Variance Reduction.

Renbo Zhao, William B. Haskell, Jiashi Feng

CoRR, 2017

Aspects of optimization with stochastic dominance.

William B. Haskell, J. George Shanthikumar, Zuo-Jun Max Shen

Ann. Oper. Res., 2017

Stochastic L-BFGS Revisited: Improved Convergence Rates and Practical Acceleration Strategies.

Renbo Zhao, William B. Haskell, Vincent Y. F. Tan

Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Dynamic programming for risk-aware sequential optimization.

Pengqian Yu, William B. Haskell, Huan Xu

Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

Risk-aware semi-Markov decision processes.

Jukka Isohataia, William B. Haskell

Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

Risk-aware Q-learning for Markov decision processes.

Wenjie Huang, William Benjamin Haskell

Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

Randomized function fitting-based empirical value iteration.

William B. Haskell, Pengqian Yu, Hiteshi Sharma, Rahul Jain

Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

A random monotone operator framework for strongly convex stochastic optimization.

William B. Haskell, Rahul Jain

Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

Sequential smoothing framework for convex-concave saddle point problems with application to large-scale constrained optimization.

Le Thi Khanh Hien, William B. Haskell

Proceedings of the 55th Annual Allerton Conference on Communication, 2017

Inexact iteration of averaged operators for non-strongly convex stochastic optimization.

William B. Haskell, Rahul Jain

Proceedings of the 55th Annual Allerton Conference on Communication, 2017

2016

Empirical Dynamic Programming.

William B. Haskell, Rahul Jain, Dileep M. Kalathil

Math. Oper. Res., 2016

Optimized Financial Systems Helps Customers Meet Their Personal Finance Goals with Optimization.

Joshua Woodruff, William B. Haskell, Alejandro Toriello

Interfaces, 2016

Ambiguity in risk preferences in robust stochastic optimization.

William B. Haskell, Lunce Fu, Maged M. Dessouky

Eur. J. Oper. Res., 2016

A dynamical systems framework for stochastic iterative optimization.

William B. Haskell, Rahul Jain, Hiteshi Sharma

Proceedings of the 55th IEEE Conference on Decision and Control, 2016

2015

A Convex Analytic Approach to Risk-Aware Markov Decision Processes.

William B. Haskell, Rahul Jain

SIAM J. Control. Optim., 2015

Robust Strategy against Unknown Risk-averse Attackers in Security Games.

Yundi Qian, William B. Haskell, Milind Tambe

Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, 2015

2014

A Dynamic Traveling Salesman Problem with Stochastic Arc Costs.

Alejandro Toriello, William B. Haskell, Michael Poremba

Oper. Res., 2014

Addressing Scalability and Robustness in Security Games with Multiple Boundedly Rational Adversaries.

Matthew Brown, William B. Haskell, Milind Tambe

Proceedings of the Decision and Game Theory for Security - 5th International Conference, 2014

Empirical policy iteration for approximate dynamic programming.

William B. Haskell, Rahul Jain, Dileep M. Kalathil

Proceedings of the 53rd IEEE Conference on Decision and Control, 2014

Online planning for optimal protector strategies in resource conservation games.

Yundi Qian, William B. Haskell, Albert Xin Jiang, Milind Tambe

Proceedings of the International conference on Autonomous Agents and Multi-Agent Systems, 2014

Building THINC: user incentivization and meeting rescheduling for energy savings.

Jun-young Kwak, Debarun Kar, William B. Haskell, Pradeep Varakantham, Milind Tambe

Proceedings of the International conference on Autonomous Agents and Multi-Agent Systems, 2014

Empirical Value Iteration for approximate dynamic programming.

William B. Haskell, Rahul Jain, Dileep M. Kalathil

Proceedings of the American Control Conference, 2014

Robust Protection of Fisheries with COmPASS.

William B. Haskell, Debarun Kar, Fei Fang, Milind Tambe, Sam Cheung, Elizabeth Denicola

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013

Stochastic Dominance-Constrained Markov Decision Processes.

William B. Haskell, Rahul Jain

SIAM J. Control. Optim., 2013

Optimization with a class of multivariate integral stochastic order constraints.

William B. Haskell, J. George Shanthikumar, Zuo-Jun Max Shen

Ann. Oper. Res., 2013

2012

Dominance-constrained Markov decision processes.

William B. Haskell, Rahul Jain

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