10 citations · 13 across the 7 of their papers we have counts for
7 papers
Certifying Lower Bounds for Risk-Sensitive Reinforcement Learning under Adversarial State Perturbations
Tong Li, Saunak Kumar Panda, Yisha Xiang
Reinforcement learning (RL) agents deployed in real-world environments are often vulnerable to adversarial perturbations in state observations, creating risks in safety-critical ap…
Statistical Inference on Gradient Flows
Tongyu Li, Alexander Giessing
Gradient-based algorithms are central to modern statistical estimation, yet their statistical analysis is often restricted to fixed-time behavior, such as convergence to a populati…
Online Statistical Inference of Constant Sample-averaged Q-Learning
Saunak Kumar Panda, Tong Li, Ruiqi Liu +1
Reinforcement learning algorithms have been widely used for decision-making tasks in various domains. However, the performance of these algorithms can be impacted by high variance…
A Statistically Reliable Optimization Framework for Bandit Experiments in Scientific Discovery
Tong Li, Travis Mandel, Goldie Phillips +4
Scientific experimentation is largely driven by statistical hypothesis testing to determine significant differences in interventions. Traditionally, experimenters allocate samples…
RIE-Greedy: Regularization-Induced Exploration for Contextual Bandits
Tong Li, Thiago de Queiroz Casanova, Eric M. Schwartz +3
Real-world contextual bandit problems with complex reward models are often tackled with iteratively trained models, such as boosting trees. However, it is difficult to directly app…
Using Adaptive Bandit Experiments to Increase and Investigate Engagement in Mental Health
Harsh Kumar, Tong Li, Jiakai Shi +11
Digital mental health (DMH) interventions, such as text-message-based lessons and activities, offer immense potential for accessible mental health support. While these intervention…
Algorithms for Adaptive Experiments that Trade-off Statistical Analysis with Reward: Combining Uniform Random Assignment and Reward Maximization
Tong Li, Jacob Nogas, Haochen Song +8
Traditional randomized A/B experiments assign arms with uniform random (UR) probability, such as 50/50 assignment to two versions of a website to discover whether one version engag…