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Daniel R. Jiang
Daniel R. Jiang
Sonstige NamenDaniel Jiang
Meta & University of Pittsburgh
Bestätigte E-Mail-Adresse bei meta.com - Startseite
Titel
Zitiert von
Zitiert von
Jahr
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
1091*2020
Optimal hour ahead bidding in the real time electricity market
DR Jiang, WB Powell
INFORMS Journal on Computing 27 (3), 525-543, 2015
1262015
An approximate dynamic programming algorithm for monotone value functions
DR Jiang, WB Powell
Operations Research 63 (6), 1489-1511, 2015
1002015
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
702014
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
592020
Risk-averse approximate dynamic programming with quantile-based risk measures
DR Jiang, WB Powell
Mathematics of Operations Research 43 (2), 554-579, 2018
57*2018
Dynamic inventory repositioning in on-demand rental networks
S Benjaafar, D Jiang, X Li, X Li
Management Science 68 (11), 7793-8514, 2022
51*2022
Feedback-based tree search for reinforcement learning
DR Jiang, E Ekwedike, H Liu
International Conference on Machine Learning (ICML), 2284-2293, 2018
402018
Shape constraints in economics and operations research
AL Johnson, DR Jiang
Statistical Science 33 (4), 527-546, 2018
222018
Practicality of nested risk measures for dynamic electric vehicle charging
DR Jiang, WB Powell
https://arxiv.org/abs/1605.02848, 2017
20*2017
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
192021
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
14*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
11*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
62023
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
42024
Aligned multi-objective optimization
Y Efroni, D Jiang, B Kretzu, J Bhandari, Z Zhu, K Ullrich
OPT 2024: Optimization for Machine Learning Workshop at NeurIPS, 2024
12024
On the linear speedup of personalized federated reinforcement learning with shared representations
G Xiong, S Wang, D Jiang, J Li
arXiv preprint arXiv:2411.15014, 2024
1*2024
Dynamic subgoal-based exploration via Bayesian optimization
Y Wang, M Poloczek, DR Jiang
Transactions on Machine Learning Research, 2023
1*2023
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