172 citations · 755 across the 58 of their papers we have counts for
58 papers
Learning by Doing: An Online Causal Reinforcement Learning Framework with Causal-Aware Policy
Ruichu Cai, Siyang Huang, Jie Qiao +6
As a key component to intuitive cognition and reasoning solutions in human intelligence, causal knowledge provides great potential for reinforcement learning (RL) agents' interpret…
Combinatorial Bandits for Maximum Value Reward Function under Max Value-Index Feedback
Yiliu Wang, Wei Chen, Milan Vojnović
We consider a combinatorial multi-armed bandit problem for maximum value reward function under maximum value and index feedback. This is a new feedback structure that lies in betwe…
Bandit Multi-linear DR-Submodular Maximization and Its Applications on Adversarial Submodular Bandits
Zongqi Wan, Jialin Zhang, Wei Chen +2
We investigate the online bandit learning of the monotone multi-linear DR-submodular functions, designing the algorithm that attains of $(1…
Combinatorial Causal Bandits without Graph Skeleton
Shi Feng, Nuoya Xiong, Wei Chen
In combinatorial causal bandits (CCB), the learning agent chooses a subset of variables in each round to intervene and collects feedback from the observed variables to minimize exp…
CohortVA: A Visual Analytic System for Interactive Exploration of Cohorts based on Historical Data
Wei Zhang, Jason K. Wong, Xumeng Wang +8
In history research, cohort analysis seeks to identify social structures and figure mobilities by studying the group-based behavior of historical figures. Prior works mainly employ…
Combinatorial Pure Exploration of Causal Bandits
Nuoya Xiong, Wei Chen
The combinatorial pure exploration of causal bandits is the following online learning task: given a causal graph with unknown causal inference distributions, in each round we choos…