7 citations · 12 across the 5 of their papers we have counts for
5 papers
LLM4Causal: Democratized Causal Tools for Everyone via Large Language Model
Haitao Jiang, Lin Ge, Yuhe Gao +2
Large Language Models (LLMs) have shown their success in language understanding and reasoning on general topics. However, their capability to perform inference based on user-specif…
A Reinforcement Learning Framework for Dynamic Mediation Analysis
Lin Ge, Jitao Wang, Chengchun Shi +2
Mediation analysis learns the causal effect transmitted via mediator variables between treatments and outcomes and receives increasing attention in various scientific domains to el…
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…
Exploratory Hidden Markov Factor Models for Longitudinal Mobile Health Data: Application to Adverse Posttraumatic Neuropsychiatric Sequelae
Lin Ge, Xinming An, Donglin Zeng +3
Adverse posttraumatic neuropsychiatric sequelae (APNS) are common among veterans and millions of Americans after traumatic exposures, resulting in substantial burdens for trauma su…
Metadata-based Multi-Task Bandits with Bayesian Hierarchical Models
Runzhe Wan, Lin Ge, Rui Song
How to explore efficiently is a central problem in multi-armed bandits. In this paper, we introduce the metadata-based multi-task bandit problem, where the agent needs to solve a l…