655 citations · 767 across the 28 of their papers we have counts for
29 papers
A Survey on Fairness in Large Language Models
Yingji Li, Mengnan Du, Rui Song +2
Large Language Models (LLMs) have shown powerful performance and development prospects and are widely deployed in the real world. However, LLMs can capture social biases from unpro…
V2X-Boosted Federated Learning for Cooperative Intelligent Transportation Systems with Contextual Client Selection
Rui Song, Lingjuan Lyu, Wei Jiang +2
Machine learning (ML) has revolutionized transportation systems, enabling autonomous driving and smart traffic services. Federated learning (FL) overcomes privacy constraints by tr…
FedBEVT: Federated Learning Bird's Eye View Perception Transformer in Road Traffic Systems
Rui Song, Runsheng Xu, Andreas Festag +2
Bird's eye view (BEV) perception is becoming increasingly important in the field of autonomous driving. It uses multi-view camera data to learn a transformer model that directly pr…
Mining the Factor Zoo: Estimation of Latent Factor Models with Sufficient Proxies
Runzhe Wan, Yingying Li, Wenbin Lu +1
Latent factor model estimation typically relies on either using domain knowledge to manually pick several observed covariates as factor proxies, or purely conducting multivariate a…
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…
On Heterogeneous Treatment Effects in Heterogeneous Causal Graphs
Richard A Watson, Hengrui Cai, Xinming An +2
Heterogeneity and comorbidity are two interwoven challenges associated with various healthcare problems that greatly hampered research on developing effective treatment and underst…
ResFed: Communication Efficient Federated Learning by Transmitting Deep Compressed Residuals
Rui Song, Liguo Zhou, Lingjuan Lyu +2
Federated learning enables cooperative training among massively distributed clients by sharing their learned local model parameters. However, with increasing model size, deploying…
Federated Learning via Decentralized Dataset Distillation in Resource-Constrained Edge Environments
Rui Song, Dai Liu, Dave Zhenyu Chen +4
In federated learning, all networked clients contribute to the model training cooperatively. However, with model sizes increasing, even sharing the trained partial models often lea…
Inference for change-plane regression
Chaeryon Kang, Hunyong Cho, Rui Song +3
A key challenge in analyzing the behavior of change-plane estimators is that the objective function has multiple minimizers. Two estimators are proposed to deal with this non-uniqu…
Transformation-Invariant Learning of Optimal Individualized Decision Rules with Time-to-Event Outcomes
Yu Zhou, Lan Wang, Rui Song +1
In many important applications of precision medicine, the outcome of interest is time to an event (e.g., death, relapse of disease) and the primary goal is to identify the optimal…
Federated Learning Framework Coping with Hierarchical Heterogeneity in Cooperative ITS
Rui Song, Liguo Zhou, Venkatnarayanan Lakshminarasimhan +2
Deep learning is a key approach for the environment perception function of Cooperative Intelligent Transportation Systems (C-ITS) with autonomous vehicles and smart traffic infrast…
Adaptive Semi-Supervised Inference for Optimal Treatment Decisions with Electronic Medical Record Data
Kevin Gunn, Wenbin Lu, Rui Song
A treatment regime is a rule that assigns a treatment to patients based on their covariate information. Recently, estimation of the optimal treatment regime that yields the greates…
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…
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…
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…
Reinforcement Learning with Heterogeneous Data: Estimation and Inference
Elynn Y. Chen, Rui Song, Michael I. Jordan
Reinforcement Learning (RL) has the promise of providing data-driven support for decision-making in a wide range of problems in healthcare, education, business, and other domains.…
Statistical Learning for Individualized Asset Allocation
Yi Ding, Yingying Li, Rui Song
We establish a high-dimensional statistical learning framework for individualized asset allocation. Our proposed methodology addresses continuous-action decision-making with a larg…
Flexible Inference of Optimal Individualized Treatment Strategy in Covariate Adjusted Randomization with Multiple Covariates
Trinetri Ghosh, Yanyuan Ma, Rui Song +1
To maximize clinical benefit, clinicians routinely tailor treatment to the individual characteristics of each patient, where individualized treatment rules are needed and are of si…
An Online Sequential Test for Qualitative Treatment Effects
Chengchun Shi, Shikai Luo, Hongtu Zhu +1
Tech companies (e.g., Google or Facebook) often use randomized online experiments and/or A/B testing primarily based on the average treatment effects to compare their new product w…
Online Testing of Subgroup Treatment Effects Based on Value Difference
Miao Yu, Wenbin Lu, Rui Song
Online A/B testing plays a critical role in the high-tech industry to guide product development and accelerate innovation. It performs a null hypothesis statistical test to determi…
On Estimating Optimal Regime for Treatment Initiation Time Based on Restricted Mean Residual Lifetime
Xin Chen, Rui Song, Jiajia Zhang +3
When to initiate treatment on patients is an important problem in many medical studies such as AIDS and cancer. In this article, we formulate the treatment initiation time problem…
Doubly Robust Inference when Combining Probability and Non-probability Samples with High-dimensional Data
Shu Yang, Jae Kwang Kim, Rui Song
Non-probability samples become increasingly popular in survey statistics but may suffer from selection biases that limit the generalizability of results to the target population. W…
A Massive Data Framework for M-Estimators with Cubic-Rate
Chengchun Shi, Wenbin Lu, Rui Song
The divide and conquer method is a common strategy for handling massive data. In this article, we study the divide and conquer method for cubic-rate estimators under the massive da…
Robust Learning for Optimal Treatment Decision with NP-Dimensionality
Chengchun Shi, Rui Song, Wenbin Lu
In order to identify important variables that are involved in making optimal treatment decision, Lu et al. (2013) proposed a penalized least squared regression framework for a fixe…