Daniel R. Jiang

31 papers A* 8Journal 22Unranked 1
YearRankTypeTitle / Venue / Authors
2025 J jnl
Aligning LLMs Toward Multi-Turn Conversational Outcomes Using Iterative PPO.
CoRR
Daniel R. Jiang, Jalaj Bhandari, Yukai Yang, Rémi Munos, Tyler Lu
2025 J jnl
Improving Generative Ad Text on Facebook using Reinforcement Learning.
CoRR
Daniel R. Jiang, Alex Nikulkov, Yu-Chia Chen, Yang Bai, Zheqing Zhu
2024 J jnl
AExGym: Benchmarks and Environments for Adaptive Experimentation.
CoRR
Jimmy Wang, Ethan Che, Daniel R. Jiang, Hongseok Namkoong
2024 J jnl
Exploiting Structure in Offline Multi-Agent RL: The Benefits of Low Interaction Rank.
CoRR
Wenhao Zhan, Scott Fujimoto, Zheqing Zhu, Jason D. Lee, Daniel R. Jiang, Yonathan Efroni
2024 J jnl
Mathematical Programming For Adaptive Experiments.
CoRR
Ethan Che, Daniel R. Jiang, Hongseok Namkoong, Jimmy Wang
2023 A* conf
2nd Workshop on Multi-Armed Bandits and Reinforcement Learning: Advancing Decision Making in E-Commerce and Beyond.
KDD
Chu Wang, Yingfei Wang, Haipeng Luo, Daniel R. Jiang, Jinghai He, Zeyu Zheng
2023 J jnl
Dynamic Subgoal-based Exploration via Bayesian Optimization.
Trans. Mach. Learn. Res.
Yijia Wang, Matthias Poloczek, Daniel R. Jiang
2023 J jnl
Faster Approximate Dynamic Programming by Freezing Slow States.
CoRR
Yijia Wang, Daniel R. Jiang
2023 J jnl
Weakly Coupled Deep Q-Networks.
CoRR
Ibrahim El Shar, Daniel R. Jiang
2022 J jnl
Dynamic Inventory Repositioning in On-Demand Rental Networks.
Manag. Sci.
Saif Benjaafar, Daniel R. Jiang, Xiang Li, Xiaobo Li
2022 A* conf
Interpretable Personalized Experimentation.
KDD
Han Wu, Sarah Tan, Weiwei Li, Mia Garrard, Adam Obeng, Drew Dimmery, Shaun Singh, Hanson Wang, Daniel R. Jiang, Eytan Bakshy
2021 J jnl
Distilling Heterogeneity: From Explanations of Heterogeneous Treatment Effect Models to Interpretable Policies.
CoRR
Han Wu, Sarah Tan, Weiwei Li, Mia Garrard, Adam Obeng, Drew Dimmery, Shaun Singh, Hanson Wang, Daniel R. Jiang, Eytan Bakshy
2021 A* conf
Multi-Armed Bandits and Reinforcement Learning: Advancing Decision Making in E-Commerce and Beyond.
KDD
Daniel R. Jiang, Haipeng Luo, Chu Wang, Yingfei Wang
2021 A* conf
Multi-Step Budgeted Bayesian Optimization with Unknown Evaluation Costs.
NeurIPS
Raul Astudillo, Daniel R. Jiang, Maximilian Balandat, Eytan Bakshy, Peter I. Frazier
2021 J jnl
Multi-Step Budgeted Bayesian Optimization with Unknown Evaluation Costs.
CoRR
Raul Astudillo, Daniel R. Jiang, Maximilian Balandat, Eytan Bakshy, Peter I. Frazier
2020 A* conf
BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization.
NeurIPS
Maximilian Balandat, Brian Karrer, Daniel R. Jiang, Samuel Daulton, Benjamin Letham, Andrew Gordon Wilson, Eytan Bakshy
2020 A* conf
Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees.
NeurIPS
Shali Jiang, Daniel R. Jiang, Maximilian Balandat, Brian Karrer, Jacob R. Gardner, Roman Garnett
2020 J jnl
Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees.
CoRR
Shali Jiang, Daniel R. Jiang, Maximilian Balandat, Brian Karrer, Jacob R. Gardner, Roman Garnett
2020 J jnl
Lookahead-Bounded Q-Learning.
CoRR
Ibrahim El Shar, Daniel R. Jiang
2020 A* conf
Lookahead-Bounded Q-learning.
ICML
Ibrahim El Shar, Daniel R. Jiang
2020 J jnl
Optimistic Monte Carlo Tree Search with Sampled Information Relaxation Dual Bounds.
Oper. Res.
Daniel R. Jiang, Lina Al-Kanj, Warren B. Powell
2019 J jnl
BoTorch: Programmable Bayesian Optimization in PyTorch.
CoRR
Maximilian Balandat, Brian Karrer, Daniel R. Jiang, Samuel Daulton, Benjamin Letham, Andrew Gordon Wilson, Eytan Bakshy
2019 J jnl
Exploration via Sample-Efficient Subgoal Design.
CoRR
Yijia Wang, Matthias Poloczek, Daniel R. Jiang
2018 A* conf
Feedback-Based Tree Search for Reinforcement Learning.
ICML
Daniel R. Jiang, Emmanuel Ekwedike, Han Liu
2018 J jnl
Feedback-Based Tree Search for Reinforcement Learning.
CoRR
Daniel R. Jiang, Emmanuel Ekwedike, Han Liu
2018 J jnl
Risk-Averse Approximate Dynamic Programming with Quantile-Based Risk Measures.
Math. Oper. Res.
Daniel R. Jiang, Warren B. Powell
2017 J jnl
Monte Carlo Tree Search with Sampled Information Relaxation Dual Bounds.
CoRR
Daniel R. Jiang, Lina Al-Kanj, Warren B. Powell
2015 J jnl
An Approximate Dynamic Programming Algorithm for Monotone Value Functions.
Oper. Res.
Daniel R. Jiang, Warren B. Powell
2015 J jnl
Optimal Hour-Ahead Bidding in the Real-Time Electricity Market with Battery Storage Using Approximate Dynamic Programming.
INFORMS J. Comput.
Daniel R. Jiang, Warren B. Powell
2015 J jnl
Risk-Averse Approximate Dynamic Programming with Quantile-Based Risk Measures.
CoRR
Daniel R. Jiang, Warren B. Powell
2014 — conf
A comparison of approximate dynamic programming techniques on benchmark energy storage problems: Does anything work?
ADPRL
Daniel R. Jiang, Thuy V. Pham, Warren B. Powell, Daniel F. Salas, Warren R. Scott