28 citations · 29 across the 3 of their papers we have counts for
6 papers
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…
Pairwise Difference Estimation of High Dimensional Partially Linear Model
Fang Han, Zhao Ren, Yuxin Zhu
This paper proposes a regularized pairwise difference approach for estimating the linear component coefficient in a partially linear model, with consistency and exact rates of conv…
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…
Discussion: Latent variable graphical model selection via convex optimization
Zhao Ren, Harrison H. Zhou
Discussion of "Latent variable graphical model selection via convex optimization" by Venkat Chandrasekaran, Pablo A. Parrilo and Alan S. Willsky [arXiv:1008.1290].