3 citations · 6 across the 3 of their papers we have counts for
7 papers
Inference in High-dimensional Multivariate Response Regression with Hidden Variables
Xin Bing, Wei Cheng, Huijie Feng +1
This paper studies the inference of the regression coefficient matrix under multivariate response linear regressions in the presence of hidden variables. A novel procedure for cons…
Detecting approximate replicate components of a high-dimensional random vector with latent structure
Xin Bing, Florentina Bunea, Marten Wegkamp
High-dimensional feature vectors are likely to contain sets of measurements that are approximate replicates of one another. In complex applications, or automated data collection, t…
Prediction in latent factor regression: Adaptive PCR and beyond
Xin Bing, Florentina Bunea, Seth Strimas-Mackey +1
This work is devoted to the finite sample prediction risk analysis of a class of linear predictors of a response from a high-dimensional random vector $X\in \math…
Adaptive Estimation in Multivariate Response Regression with Hidden Variables
Xin Bing, Yang Ning, Yaosheng Xu
This paper studies the estimation of the coefficient matrix $\Ttheta$ in multivariate regression with hidden variables, $Y = (\Ttheta)^TX + (B^*)^TZ + E$, where is a -dimens…
Optimal estimation of sparse topic models
Xin Bing, Florentina Bunea, Marten Wegkamp
Topic models have become popular tools for dimension reduction and exploratory analysis of text data which consists in observed frequencies of a vocabulary of words in docu…
Inference in latent factor regression with clusterable features
Xin Bing, Florentina Bunea, Marten Wegkamp
Regression models, in which the observed features and the response depend, jointly, on a lower dimensional, unobserved, latent vector , with $K<…