15 citations · 48 across the 19 of their papers we have counts for
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cs.LG2022★ 1 cited
Towards Scalable and Robust Structured Bandits: A Meta-Learning Framework
Runzhe Wan, Lin Ge, Rui Song
Online learning in large-scale structured bandits is known to be challenging due to the curse of dimensionality. In this paper, we propose a unified meta-learning framework for a g…
cs.LG2022★ 1 cited
Safe Exploration for Efficient Policy Evaluation and Comparison
Runzhe Wan, Branislav Kveton, Rui Song
High-quality data plays a central role in ensuring the accuracy of policy evaluation. This paper initiates the study of efficient and safe data collection for bandit policy evaluat…
stat.ML2022★ 1 cited
A Multi-Agent Reinforcement Learning Framework for Off-Policy Evaluation in Two-sided Markets
Chengchun Shi, Runzhe Wan, Ge Song +3
The two-sided markets such as ride-sharing companies often involve a group of subjects who are making sequential decisions across time and/or location. With the rapid development o…