60 citations · 172 across the 17 of their papers we have counts for
9 papers · 1 filter
ReBoot: Distributed statistical learning via refitting bootstrap samples
Yumeng Wang, Ziwei Zhu, Xuming He
In this paper, we propose a one-shot distributed learning algorithm via refitting bootstrap samples, which we refer to as ReBoot. ReBoot refits a new model to mini-batches of boots…
Best subset selection is robust against design dependence
Yongyi Guo, Ziwei Zhu, Jianqing Fan
Best subset selection (BSS) is widely known as the holy grail for high-dimensional variable selection. Nevertheless, the notorious NP-hardness of BSS substantially restricts its pr…
Learning Markov models via low-rank optimization
Ziwei Zhu, Xudong Li, Mengdi Wang +1
Modeling unknown systems from data is a precursor of system optimization and sequential decision making. In this paper, we focus on learning a Markov model from a single trajectory…
High-dimensional principal component analysis with heterogeneous missingness
Ziwei Zhu, Tengyao Wang, Richard J. Samworth
We study the problem of high-dimensional Principal Component Analysis (PCA) with missing observations. In simple, homogeneous missingness settings with a noise level of constant or…
Robust high dimensional factor models with applications to statistical machine learning
Jianqing Fan, Kaizheng Wang, Yiqiao Zhong +1
Factor models are a class of powerful statistical models that have been widely used to deal with dependent measurements that arise frequently from various applications from genomic…
Principal component analysis for big data
Jianqing Fan, Qiang Sun, Wen-Xin Zhou +1
Big data is transforming our world, revolutionizing operations and analytics everywhere, from financial engineering to biomedical sciences. The complexity of big data often makes d…
Generalized High-Dimensional Trace Regression via Nuclear Norm Regularization
Jianqing Fan, Wenyan Gong, Ziwei Zhu
We study the generalized trace regression with a near low-rank regression coefficient matrix, which extends notion of sparsity for regression coefficient vectors. Specifically, giv…
Taming heavy-tailed features by shrinkage
Ziwei Zhu, Wenjing Zhou
In this work, we focus on a variant of the generalized linear model (GLM) called corrupted GLM (CGLM) with heavy-tailed features and responses. To robustify the statistical inferen…
Heterogeneity Adjustment with Applications to Graphical Model Inference
Jianqing Fan, Han Liu, Weichen Wang +1
Heterogeneity is an unwanted variation when analyzing aggregated datasets from multiple sources. Though different methods have been proposed for heterogeneity adjustment, no system…