Publications (18)
A Tree-based Model Averaging Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sources
Xiaoqing Tan, Chung-Chou H. Chang, Ling Zhou +1
Accurately estimating personalized treatment effects within a study site (e.g., a hospital) has been challenging due to limited sample size. Furthermore, privacy considerations and…
MVPipe: Enabling Lightweight Updates and Fast Convergence in Hierarchical Heavy Hitter Detection
Lu Tang, Qun Huang, Patrick P. C. Lee
Finding hierarchical heavy hitters (HHHs) (i.e., hierarchical aggregates with exceptionally huge amounts of traffic) is critical to network management, yet it is often challenged b…
Distributed Simultaneous Inference in Generalized Linear Models via Confidence Distribution
Lu Tang, Ling Zhou, Peter X. -K. Song
We propose a distributed method for simultaneous inference for datasets with sample size much larger than the number of covariates, i.e., N >> p, in the generalized linear models f…
RepLLM: Toward Automatically Reproducing Network Research Results
Yining Jiang, Yunxin Xu, Wenyun Xu +14
Result reproduction of computer networking research is challenging as the scarcity of open-source implementations and the complexity of heterogeneous system architectures. Even tho…
Covariate-guided Bayesian mixture model for multivariate time series
Haoyi Fu, Lu Tang, Ori Rosen +3
With rapid development of techniques to measure brain activity and structure, statistical methods for analyzing modern brain-imaging play an important role in the advancement of sc…
Sensitivity Analysis of Causal Treatment Effect Estimation for Clustered Observational Data with Unmeasured Confounding
Yang Ou, Lu Tang, Chung-Chou H. Chang
Identifying causal treatment (or exposure) effects in observational studies requires the data to satisfy the unconfoundedness assumption which is not testable using the observed da…
RISE: Robust Individualized Decision Learning with Sensitive Variables
Xiaoqing Tan, Zhengling Qi, Christopher W. Seymour +1
This paper introduces RISE, a robust individualized decision learning framework with sensitive variables, where sensitive variables are collectible data and important to the interv…
Outcome-Guided Disease Subtyping for High-Dimensional Omics Data
Peng Liu, Yusi Fang, Zhao Ren +2
High-throughput microarray and sequencing technology have been used to identify disease subtypes that could not be observed otherwise by using clinical variables alone. The classic…
Fletch: File-System Metadata Caching in Programmable Switches
Qingxiu Liu, Jiazhen Cai, Siyuan Sheng +4
Fast and scalable metadata management across multiple metadata servers is crucial for distributed file systems to handle numerous files and directories. Client-side caching of freq…
A Fast and Compact Invertible Sketch for Network-Wide Heavy Flow Detection
Lu Tang, Qun Huang, Patrick P. C. Lee
Fast detection of heavy flows (e.g., heavy hitters and heavy changers) in massive network traffic is challenging due to the stringent requirements of fast packet processing and lim…
A sparse negative binomial mixture model for clustering RNA-seq count data
Tanbin Rahman, Yujia Li, Tianzhou Ma +2
Clustering with variable selection is a challenging yet critical task for modern small-n-large-p data. Existing methods based on sparse Gaussian mixture models or sparse K-means pr…
Method of Contraction-Expansion (MOCE) for Simultaneous Inference in Linear Models
Fei Wang, Ling Zhou, Lu Tang +1
Simultaneous inference after model selection is of critical importance to address scientific hypotheses involving a set of parameters. In this paper, we consider high-dimensional l…
Bayesian response adaptive randomization design with a composite endpoint of mortality and morbidity
Zhongying Xu, Andriy I. Bandos, Tianzhou Ma +3
Allocating patients to treatment arms during a trial based on the observed responses accumulated prior to the decision point, and sequential adaptation of this allocation,, could m…
Nuclear charge radius predictions by kernel ridge regression with odd-even effects
Lu Tang, Zhen-Hua Zhang
The extended kernel ridge regression (EKRR) method with odd-even effects was adopted to improve the description of the nuclear charge radius using five commonly used nuclear models…
Sketching AI Concepts with Capabilities and Examples: AI Innovation in the Intensive Care Unit
Nur Yildirim, Susanna Zlotnikov, Deniz Sayar +14
Advances in artificial intelligence (AI) have enabled unprecedented capabilities, yet innovation teams struggle when envisioning AI concepts. Data science teams think of innovation…
Examining Potential Usability and Health Beliefs Among Young Adults Using a Conversational Agent for HPV Vaccine Counseling
Muhammad Amith, Rebecca Lin, Rachel Cunningham +6
The human papillomavirus (HPV) vaccine is the most effective way to prevent HPV-related cancers. Integrating provider vaccine counseling is crucial to improving HPV vaccine complet…
Static Algorithm, Evolving Epidemic: Understanding the Potential of Human-AI Risk Assessment to Support Regional Overdose Prevention
Venkatesh Sivaraman, Yejun Kwak, Courtney Kuza +6
Drug overdose deaths, including those due to prescription opioids, represent a critical public health issue in the United States and worldwide. Artificial intelligence (AI) approac…
Argo: An efficient verification framework for distributed in-network computing
Mingyuan Song, Huan Shen, Jinghui Jiang +7
Distributed in-network programs are increasingly deployed in data centers for their performance benefits, but shifting application logic to switches also enlarges the failure domai…