224 citations · 344 across the 14 of their papers we have counts for
6 papers · 1 filter
Simultaneous Inference in Multiple Matrix-Variate Graphs for High-Dimensional Neural Recordings
Zongge Liu, Heejong Bong, Zhao Ren +2
We study simultaneous inference for multiple matrix-variate Gaussian graphical models in high-dimensional settings. Such models arise when spatiotemporal data are collected across…
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…
User-Friendly Covariance Estimation for Heavy-Tailed Distributions
Yuan Ke, Stanislav Minsker, Zhao Ren +2
We offer a survey of recent results on covariance estimation for heavy-tailed distributions. By unifying ideas scattered in the literature, we propose user-friendly methods that fa…
Variable screening with multiple studies
Tianzhou Ma, Zhao Ren, George C. Tseng
Advancement in technology has generated abundant high-dimensional data that allows integration of multiple relevant studies. Due to their huge computational advantage, variable scr…
Tuning-Free Heterogeneity Pursuit in Massive Networks
Zhao Ren, Yongjian Kang, Yingying Fan +1
Heterogeneity is often natural in many contemporary applications involving massive data. While posing new challenges to effective learning, it can play a crucial role in powering m…
Asymptotically Normal and Efficient Estimation of Covariate-Adjusted Gaussian Graphical Model
Mengjie Chen, Zhao Ren, Hongyu Zhao +1
A tuning-free procedure is proposed to estimate the covariate-adjusted Gaussian graphical model. For each finite subgraph, this estimator is asymptotically normal and efficient. As…