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ORCIDWilliam B. Haskell 0001
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- affiliation: Purdue University, West Lafayette, IN, USA
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2020 – today
- 2024
[j25]Bo Wei, William B. Haskell
, Sixiang Zhao:
Correction to: The CoMirror algorithm with random constraint sampling for convex semi-infinite programming. Ann. Oper. Res. 332(1): 1247 (2024)- [j24]Le Thi Khanh Hien, Renbo Zhao, William B. Haskell:
An Inexact Primal-Dual Smoothing Framework for Large-Scale Non-Bilinear Saddle Point Problems. J. Optim. Theory Appl. 200(1): 34-67 (2024) - [j23]Gemma Berenguer, William B. Haskell, Lei Li:
Managing Volunteers and Paid Workers in a Nonprofit Operation. Manag. Sci. 70(8): 5298-5316 (2024) - [j22]Xuejun Zhao, William B. Haskell, Guodong Yu:
Supply Chain Contracts in the Small Data Regime. Manuf. Serv. Oper. Manag. 26(4): 1387-1401 (2024) - 2022
- [j21]Songhao Wang, Szu Hui Ng, William Benjamin Haskell:
A Multilevel Simulation Optimization Approach for Quantile Functions. INFORMS J. Comput. 34(1): 569-585 (2022) - [j20]Xun Zhang, William B. Haskell, Zhisheng Ye:
A Unifying Framework for Variance-Reduced Algorithms for Findings Zeroes of Monotone operators. J. Mach. Learn. Res. 23: 60:1-60:44 (2022) - [j19]William B. Haskell, Huifu Xu, Wenjie Huang:
Preference Robust Optimization for Choice Functions on the Space of CDFs. SIAM J. Optim. 32(2): 1446-1470 (2022) - [j18]Jukka Isohätälä, William B. Haskell:
Risk Aware Minimum Principle for Optimal Control of Stochastic Differential Equations. IEEE Trans. Autom. Control. 67(10): 5102-5117 (2022) - [i11]Shiping Shao, Abhishek Gupta, William B. Haskell:
Robustness to Modeling Errors in Risk-Sensitive Markov Decision Problems with Markov Risk Measures. CoRR abs/2209.12937 (2022) - [i10]Xuejun Zhao, Ruihao Zhu, William B. Haskell:
Learning to Price Supply Chain Contracts against a Learning Retailer. CoRR abs/2211.04586 (2022) - 2021
- [j17]Abhishek Gupta, William B. Haskell:
Convergence of Recursive Stochastic Algorithms Using Wasserstein Divergence. SIAM J. Math. Data Sci. 3(4): 1141-1167 (2021) - [j16]Wenjie Huang, William B. Haskell:
Stochastic Approximation for Risk-Aware Markov Decision Processes. IEEE Trans. Autom. Control. 66(3): 1314-1320 (2021) - 2020
- [j15]Bo Wei, William B. Haskell, Sixiang Zhao:
The CoMirror algorithm with random constraint sampling for convex semi-infinite programming. Ann. Oper. Res. 295(2): 809-841 (2020) - [j14]Bo Wei, William B. Haskell, Sixiang Zhao:
An inexact primal-dual algorithm for semi-infinite programming. Math. Methods Oper. Res. 91(3): 501-544 (2020) - [j13]William B. Haskell, Rahul Jain, Hiteshi Sharma, Pengqian Yu:
A Universal Empirical Dynamic Programming Algorithm for Continuous State MDPs. IEEE Trans. Autom. Control. 65(1): 115-129 (2020) - [c21]Wenjie Huang, Pham Viet Hai, William Benjamin Haskell:
Model and Reinforcement Learning for Markov Games with Risk Preferences. AAAI 2020: 2022-2029 - [i9]Abhishek Gupta, William B. Haskell:
Convergence of Recursive Stochastic Algorithms using Wasserstein Divergence. CoRR abs/2003.11403 (2020)
2010 – 2019
- 2019
- [c20]Renbo Zhao, William B. Haskell, Vincent Y. F. Tan:
An Optimal Algorithm for Stochastic Three-Composite Optimization. AISTATS 2019: 428-437 - [c19]Hiteshi Sharma, Rahul Jain, William B. Haskell:
Empirical Algorithms for General Stochastic Systems with Continuous States and Actions. CDC 2019: 6344-6349 - [i8]Wenjie Huang, Pham Viet Hai, William Benjamin Haskell:
Model and Algorithm for Time-Consistent Risk-Aware Markov Games. CoRR abs/1901.04882 (2019) - [i7]Xun Zhang, William B. Haskell, Zhisheng Ye:
A Unifying Framework for Variance Reduction Algorithms for Finding Zeroes of Monotone Operators. CoRR abs/1906.09437 (2019) - 2018
- [j12]William B. Haskell, Alejandro Toriello:
Modeling Stochastic Dominance as Infinite-Dimensional Constraint Systems via the Strassen Theorem. J. Optim. Theory Appl. 178(3): 726-742 (2018) - [j11]Pengqian Yu, William B. Haskell, Huan Xu:
Approximate Value Iteration for Risk-Aware Markov Decision Processes. IEEE Trans. Autom. Control. 63(9): 3135-3142 (2018) - [j10]Renbo Zhao, William B. Haskell, Vincent Y. F. Tan:
Stochastic L-BFGS: Improved Convergence Rates and Practical Acceleration Strategies. IEEE Trans. Signal Process. 66(5): 1155-1169 (2018) - [c18]Songhao Wang, Szu Hui Ng, William Benjamin Haskell:
Quantile simulation Optimization with stochastic Co-Kriging Model. WSC 2018: 2119-2130 - [i6]Zhi Chen, Pengqian Yu, William B. Haskell:
Distributionally Robust Optimization for Sequential Decision Making. CoRR abs/1801.04745 (2018) - [i5]Wenjie Huang, William Benjamin Haskell:
Stochastic Approximation for Risk-aware Markov Decision Processes. CoRR abs/1805.04238 (2018) - [i4]William Benjamin Haskell, Wenjie Huang, Huifu Xu:
Preference Elicitation and Robust Optimization with Multi-Attribute Quasi-Concave Choice Functions. CoRR abs/1805.06632 (2018) - 2017
- [j9]William B. Haskell, J. George Shanthikumar, Zuo-Jun Max Shen:
Aspects of optimization with stochastic dominance. Ann. Oper. Res. 253(1): 247-273 (2017) - [j8]William B. Haskell, J. George Shanthikumar, Zuo-Jun Max Shen:
Primal-Dual Algorithms for Optimization with Stochastic Dominance. SIAM J. Optim. 27(1): 34-66 (2017) - [c17]Le Thi Khanh Hien, William B. Haskell:
Sequential smoothing framework for convex-concave saddle point problems with application to large-scale constrained optimization. Allerton 2017: 1176-1183 - [c16]William B. Haskell, Rahul Jain:
Inexact iteration of averaged operators for non-strongly convex stochastic optimization. Allerton 2017: 1184-1191 - [c15]William B. Haskell, Pengqian Yu, Hiteshi Sharma, Rahul Jain:
Randomized function fitting-based empirical value iteration. CDC 2017: 2467-2472 - [c14]William B. Haskell, Rahul Jain:
A random monotone operator framework for strongly convex stochastic optimization. CDC 2017: 3763-3768 - [c13]Jukka Isohataia, William B. Haskell:
Risk-aware semi-Markov decision processes. CDC 2017: 4303-4308 - [c12]Wenjie Huang, William Benjamin Haskell:
Risk-aware Q-learning for Markov decision processes. CDC 2017: 4928-4933 - [c11]Pengqian Yu, William B. Haskell, Huan Xu:
Dynamic programming for risk-aware sequential optimization. CDC 2017: 4934-4939 - [c10]Renbo Zhao, William B. Haskell, Vincent Y. F. Tan:
Stochastic L-BFGS Revisited: Improved Convergence Rates and Practical Acceleration Strategies. UAI 2017 - [i3]Pengqian Yu, William B. Haskell, Huan Xu:
Approximate Value Iteration for Risk-aware Markov Decision Processes. CoRR abs/1701.01290 (2017) - [i2]Renbo Zhao, William B. Haskell, Vincent Y. F. Tan:
Stochastic L-BFGS Revisited: Improved Convergence Rates and Practical Acceleration Strategies. CoRR abs/1704.00116 (2017) - [i1]Renbo Zhao, William B. Haskell, Jiashi Feng:
A Unified Framework for Stochastic Matrix Factorization via Variance Reduction. CoRR abs/1705.06884 (2017) - 2016
- [j7]William B. Haskell, Lunce Fu, Maged M. Dessouky:
Ambiguity in risk preferences in robust stochastic optimization. Eur. J. Oper. Res. 254(1): 214-225 (2016) - [j6]Joshua Woodruff, William B. Haskell, Alejandro Toriello:
Optimized Financial Systems Helps Customers Meet Their Personal Finance Goals with Optimization. Interfaces 46(4): 345-359 (2016) - [j5]William B. Haskell, Rahul Jain, Dileep M. Kalathil:
Empirical Dynamic Programming. Math. Oper. Res. 41(2): 402-429 (2016) - [c9]William B. Haskell, Rahul Jain, Hiteshi Sharma:
A dynamical systems framework for stochastic iterative optimization. CDC 2016: 4504-4509 - 2015
- [j4]William B. Haskell, Rahul Jain:
A Convex Analytic Approach to Risk-Aware Markov Decision Processes. SIAM J. Control. Optim. 53(3): 1569-1598 (2015) - [c8]Yundi Qian, William B. Haskell, Milind Tambe:
Robust Strategy against Unknown Risk-averse Attackers in Security Games. AAMAS 2015: 1341-1349 - 2014
- [j3]Alejandro Toriello, William B. Haskell, Michael Poremba:
A Dynamic Traveling Salesman Problem with Stochastic Arc Costs. Oper. Res. 62(5): 1107-1125 (2014) - [c7]William B. Haskell, Debarun Kar, Fei Fang, Milind Tambe, Sam Cheung, Elizabeth Denicola:
Robust Protection of Fisheries with COmPASS. AAAI 2014: 2978-2983 - [c6]William B. Haskell, Rahul Jain, Dileep M. Kalathil:
Empirical Value Iteration for approximate dynamic programming. ACC 2014: 495-500 - [c5]Yundi Qian, William B. Haskell, Albert Xin Jiang, Milind Tambe:
Online planning for optimal protector strategies in resource conservation games. AAMAS 2014: 733-740 - [c4]Jun-young Kwak, Debarun Kar, William B. Haskell, Pradeep Varakantham, Milind Tambe:
Building THINC: user incentivization and meeting rescheduling for energy savings. AAMAS 2014: 925-932 - [c3]William B. Haskell, Rahul Jain, Dileep M. Kalathil:
Empirical policy iteration for approximate dynamic programming. CDC 2014: 6573-6578 - [c2]Matthew Brown, William B. Haskell, Milind Tambe:
Addressing Scalability and Robustness in Security Games with Multiple Boundedly Rational Adversaries. GameSec 2014: 23-42 - 2013
- [j2]William B. Haskell, J. George Shanthikumar, Zuo-Jun Max Shen:
Optimization with a class of multivariate integral stochastic order constraints. Ann. Oper. Res. 206(1): 147-162 (2013) - [j1]William B. Haskell, Rahul Jain:
Stochastic Dominance-Constrained Markov Decision Processes. SIAM J. Control. Optim. 51(1): 273-303 (2013) - 2012
- [c1]William B. Haskell, Rahul Jain:
Dominance-constrained Markov decision processes. CDC 2012: 5991-5996
Coauthor Index
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