23 citations · 32 across the 6 of their papers we have counts for
6 papers · 1 filter
Off-Policy Selection for Initiating Human-Centric Experimental Design
Ge Gao, Xi Yang, Qitong Gao +3
In human-centric tasks such as healthcare and education, the heterogeneity among patients and students necessitates personalized treatments and instructional interventions. While r…
Off-Policy Evaluation for Human Feedback
Qitong Gao, Ge Gao, Juncheng Dong +3
Off-policy evaluation (OPE) is important for closing the gap between offline training and evaluation of reinforcement learning (RL), by estimating performance and/or rank of target…
An Offline Time-aware Apprenticeship Learning Framework for Evolving Reward Functions
Xi Yang, Ge Gao, Min Chi
Apprenticeship learning (AL) is a process of inducing effective decision-making policies via observing and imitating experts' demonstrations. Most existing AL approaches, however,…
HOPE: Human-Centric Off-Policy Evaluation for E-Learning and Healthcare
Ge Gao, Song Ju, Markel Sanz Ausin +1
Reinforcement learning (RL) has been extensively researched for enhancing human-environment interactions in various human-centric tasks, including e-learning and healthcare. Since…
Variational Latent Branching Model for Off-Policy Evaluation
Qitong Gao, Ge Gao, Min Chi +1
Model-based methods have recently shown great potential for off-policy evaluation (OPE); offline trajectories induced by behavioral policies are fitted to transitions of Markov dec…
Early Performance Prediction using Interpretable Patterns in Programming Process Data
Ge Gao, Samiha Marwan, Thomas W. Price
Instructors have limited time and resources to help struggling students, and these resources should be directed to the students who most need them. To address this, researchers hav…