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Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees

Jun 29, 2020
Shali Jiang, Daniel R. Jiang, Maximilian Balandat, Brian Karrer, Jacob R. Gardner, Roman Garnett

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Lookahead-Bounded Q-Learning

Jun 28, 2020
Ibrahim El Shar, Daniel R. Jiang

* To appear in proceedings of the 37th International Conference on Machine Learning 

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Exploration via Sample-Efficient Subgoal Design

Oct 21, 2019
Yijia Wang, Matthias Poloczek, Daniel R. Jiang

* Presented at TARL, ICLR 2019 workshop 

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BoTorch: Programmable Bayesian Optimization in PyTorch

Oct 14, 2019
Maximilian Balandat, Brian Karrer, Daniel R. Jiang, Samuel Daulton, Benjamin Letham, Andrew Gordon Wilson, Eytan Bakshy

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Feedback-Based Tree Search for Reinforcement Learning

May 15, 2018
Daniel R. Jiang, Emmanuel Ekwedike, Han Liu

* 19 pages, to be presented at ICML 2018 

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Risk-Averse Approximate Dynamic Programming with Quantile-Based Risk Measures

May 09, 2017
Daniel R. Jiang, Warren B. Powell

* 39 pages, 7 figures 

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Monte Carlo Tree Search with Sampled Information Relaxation Dual Bounds

Apr 20, 2017
Daniel R. Jiang, Lina Al-Kanj, Warren B. Powell

* 33 pages, 6 figures 

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