Daniel R. Jiang

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Warrren B PowellPrinceton UniversityVerified email at princeton.edu
Maximilian BalandatResearch Scientist Manager, MetaVerified email at fb.com
Eytan BakshyResearch Director, MetaVerified email at fb.com
Brian KarrerResearch Science Manager, MetaVerified email at fb.com
Andrew Gordon WilsonNew York UniversityVerified email at cims.nyu.edu
Samuel (Sam) DaultonResearch Scientist - Meta, University of OxfordVerified email at fb.com
Xiaobo LiAssistant Professor of Industrial Engineering, National University of SingaporeVerified email at nus.edu.sg
Saif BenjaafarUniversity of MinnesotaVerified email at umn.edu
Lina Al-KanjAssociate Research Scholar, Princeton UniversityVerified email at princeton.edu
Han LiuAssociate Professor, Department of Computer Science, Northwestern UniversityVerified email at princeton.edu
Emmanuel EkwedikeMachine Learning Research ScientistVerified email at princeton.edu
Roman GarnettWashington University in St. LouisVerified email at wustl.edu
Shali JiangFacebookVerified email at wustl.edu
Jacob GardnerUniversity of PennsylvaniaVerified email at seas.upenn.edu
Andrew L JohnsonDepartment of Industrial and Systems Engineering, Texas A&M and Amazon.comVerified email at tamu.edu
Yijia WangUniversity of PittsburghVerified email at pitt.edu
Sarah TanFacebookVerified email at fb.com
Peter I FrazierAssociate Professor of Operations Research and Information Engineering, Cornell UniversityVerified email at cornell.edu
Raul AstudilloPh.D. Student, Cornell UniversityVerified email at cornell.edu
Matthias PoloczekPrincipal Scientist at AmazonVerified email at cornell.edu

Daniel R. Jiang

Meta Core Data Science, University of Pittsburgh

Verified email at pitt.edu - Homepage

approximate dynamic programming reinforcement learning Bayesian optimization


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BoTorch: A framework for efficient Monte-Carlo Bayesian optimization M Balandat, B Karrer, D Jiang, S Daulton, B Letham, AG Wilson, E Bakshy Advances in Neural Information Processing Systems 33, 2020	285*	2020
Optimal hour ahead bidding in the real time electricity market with battery storage using approximate dynamic programming DR Jiang, WB Powell INFORMS Journal on Computing 27 (3), 525-543, 2015	93	2015
An approximate dynamic programming algorithm for monotone value functions DR Jiang, WB Powell Operations Research 63 (6), 1489-1511, 2015	73	2015
A comparison of approximate dynamic programming techniques on benchmark energy storage problems: Does anything work? DR Jiang, TV Pham, WB Powell, DF Salas, WR Scott 2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement …, 2014	58	2014
Risk-averse approximate dynamic programming with quantile-based risk measures DR Jiang, WB Powell Mathematics of Operations Research 43 (2), 554-579, 2018	44*	2018
Dynamic inventory repositioning in on-demand rental networks S Benjaafar, D Jiang, X Li, X Li Management Science, 2022	31*	2022
Feedback-based tree search for reinforcement learning DR Jiang, E Ekwedike, H Liu International Conference on Machine Learning (ICML), 2284-2293, 2018	29	2018
Optimistic Monte Carlo tree search with sampled information relaxation dual bounds DR Jiang, L Al-Kanj, WB Powell Operations Research 68 (6), 1678-1697, 2020	14*	2020
Practicality of nested risk measures for dynamic electric vehicle charging DR Jiang, WB Powell https://arxiv.org/abs/1605.02848, 2017	14	2017
Efficient nonmyopic Bayesian optimization via one-shot multi-step trees S Jiang, DR Jiang, M Balandat, B Karrer, JR Gardner, R Garnett Advances in Neural Information Processing Systems 33, 2020	13	2020
Shape constraints in economics and operations research AL Johnson, DR Jiang Statistical Science 33 (4), 527-546, 2018	12	2018
Lookahead-bounded Q-learning IE Shar, DR Jiang International Conference on Machine Learning (ICML), 2020	6*	2020
Method for bidding battery storage into hour-ahead energy markets WB Powell, DR Jiang US Patent 9,965,802, 2018	3	2018
Multi-step budgeted Bayesian optimization with unknown evaluation costs R Astudillo, D Jiang, M Balandat, E Bakshy, P Frazier Advances in Neural Information Processing Systems 34, 2021	2	2021
Interpretable personalized experimentation H Wu, S Tan, W Li, M Garrard, A Obeng, D Dimmery, S Singh, H Wang, ... Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021	1*	2021
Structured actor-critic for managing public health points-of-dispensing Y Wang, DR Jiang arXiv preprint arXiv:1806.02490, 2019	1	2019
Multi-armed bandits and reinforcement learning: Advancing decision making in e-commerce and beyond D Jiang, H Luo, C Wang, Y Wang Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021		2021
Exploration via sample-efficient subgoal design Y Wang, M Poloczek, DR Jiang arXiv preprint arXiv:1910.09143, 2019		2019

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