Daniel R. Jiang

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Eytan BakshyResearch Director, MetaDirección de correo verificada de fb.com
Maximilian BalandatResearch Scientist Manager, MetaDirección de correo verificada de meta.com
Warrren B PowellPrinceton UniversityDirección de correo verificada de princeton.edu
Brian KarrerResearch Science Manager, MetaDirección de correo verificada de fb.com
Andrew Gordon WilsonNew York UniversityDirección de correo verificada de cims.nyu.edu
Samuel DaultonResearch Scientist, MetaDirección de correo verificada de meta.com
Xiaobo LiAssistant Professor of Industrial Engineering, National University of SingaporeDirección de correo verificada de nus.edu.sg
Saif BenjaafarUniversity of MinnesotaDirección de correo verificada de umn.edu
Lina Al-KanjAssociate Research Scholar, Princeton UniversityDirección de correo verificada de princeton.edu
Ibrahim El SharMachine Learning Scientist, PhD at University of PittsburghDirección de correo verificada de pitt.edu
Roman GarnettWashington University in St. LouisDirección de correo verificada de wustl.edu
Shali JiangFacebookDirección de correo verificada de wustl.edu
Jacob GardnerUniversity of PennsylvaniaDirección de correo verificada de seas.upenn.edu
Peter I FrazierAssociate Professor of Operations Research and Information Engineering, Cornell UniversityDirección de correo verificada de cornell.edu
Raul AstudilloPostdoctoral Scholar, California Institute of TechnologyDirección de correo verificada de caltech.edu
Han LiuOrrington Lunt Professor of Computer Science, Statistics and Data Science, Northwestern UniversityDirección de correo verificada de northwestern.edu
Emmanuel EkwedikeMachine Learning Research ScientistDirección de correo verificada de princeton.edu
Shaun SinghResearch Engineer, FacebookDirección de correo verificada de fb.com
Drew DimmeryHertie SchoolDirección de correo verificada de hertie-school.org
Sarah TanSalesforce / Cornell UniversityDirección de correo verificada de cornell.edu

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Daniel R. Jiang

Otros nombresDaniel Jiang

Meta & University of Pittsburgh

Dirección de correo verificada de meta.com - Página principal

reinforcement learning Bayesian optimization sequential decision making


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
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	1001*	2020
Optimal hour ahead bidding in the real time electricity market DR Jiang, WB Powell INFORMS Journal on Computing 27 (3), 525-543, 2015	124	2015
An approximate dynamic programming algorithm for monotone value functions DR Jiang, WB Powell Operations Research 63 (6), 1489-1511, 2015	96	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	69	2014
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	55	2020
Risk-averse approximate dynamic programming with quantile-based risk measures DR Jiang, WB Powell Mathematics of Operations Research 43 (2), 554-579, 2018	55*	2018
Dynamic inventory repositioning in on-demand rental networks S Benjaafar, D Jiang, X Li, X Li Management Science 68 (11), 7793-8514, 2022	50*	2022
Feedback-based tree search for reinforcement learning DR Jiang, E Ekwedike, H Liu International Conference on Machine Learning (ICML), 2284-2293, 2018	38	2018
Shape constraints in economics and operations research AL Johnson, DR Jiang Statistical Science 33 (4), 527-546, 2018	20	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	19	2021
Practicality of nested risk measures for dynamic electric vehicle charging DR Jiang, WB Powell https://arxiv.org/abs/1605.02848, 2017	19*	2017
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	17*	2020
Lookahead-bounded Q-learning IE Shar, DR Jiang International Conference on Machine Learning (ICML), 2020	13*	2020
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	10*	2021
Weakly coupled deep Q-networks IE Shar, DR Jiang Advances in Neural Information Processing Systems 37, 2023	6*	2023
On noisy evaluation in federated hyperparameter tuning K Kuo, P Thaker, M Khodak, J Nguyen, D Jiang, A Talwalkar, V Smith Proceedings of Machine Learning and Systems 5, 2023	5	2023
Pearl: A production-ready reinforcement learning agent Z Zhu, RS Braz, J Bhandari, D Jiang, Y Wan, Y Efroni, L Wang, R Xu, ... Journal of Machine Learning Research, 2024	2	2024
Personalized federated reinforcement learning with shared representations G Xiong, S Wang, D Jiang, J Li Deployable RL Workshop at RLC 2024, 2024	1	2024
Dynamic subgoal-based exploration via Bayesian optimization Y Wang, M Poloczek, DR Jiang Transactions on Machine Learning Research, 2023	1*	2023
Faster approximate dynamic programming by freezing slow states Y Wang, DR Jiang arXiv preprint arXiv:2301.00922, 2023	1	2023

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