b'Cun-Hui Zhang'

research

∙ 03/03/2023

Rate adaptive estimation of the center of a symmetric distribution

Given univariate random variables Y_1, …, Y_n with the Uniform(θ_0 - 1, ...

0 Yu-Chun Kao, et al. ∙

research

∙ 10/29/2021

CP Factor Model for Dynamic Tensors

Observations in various applications are frequently represented as a tim...

0 Yuefeng Han, et al. ∙

research

∙ 08/10/2021

Tensor Principal Component Analysis in High Dimensional CP Models

The CP decomposition for high dimensional non-orthogonal spike tensors i...

0 Yuefeng Han, et al. ∙

research

∙ 07/08/2021

Asymptotic normality of robust M-estimators with convex penalty

This paper develops asymptotic normality results for individual coordina...

0 Pierre C. Bellec, et al. ∙

research

∙ 03/17/2021

Simultaneous Decorrelation of Matrix Time Series

We propose a contemporaneous bilinear transformation for matrix time ser...

0 Yuefeng Han, et al. ∙

research

∙ 11/13/2020

Rank Determination in Tensor Factor Model

Factor model is an appealing and effective analytic tool for high-dimens...

0 Yuefeng Han, et al. ∙

research

∙ 11/13/2020

Adaptive Estimation In High-Dimensional Additive Models With Multi-Resolution Group Lasso

In additive models with many nonparametric components, a number of regul...

0 Yisha Yao, et al. ∙

research

∙ 06/04/2020

Tensor Factor Model Estimation by Iterative Projection

Tensor time series, which is a time series consisting of tensorial obser...

0 Yuefeng Han, et al. ∙

research

∙ 01/20/2020

Confidence intervals for multiple isotonic regression and other monotone models

We consider the problem of constructing pointwise confidence intervals i...

0 Hang Deng, et al. ∙

research

∙ 12/26/2019

Second order Poincaré inequalities and de-biasing arbitrary convex regularizers when p/n → γ

A new Central Limit Theorem (CLT) is developed for random variables of t...

0 Pierre C. Bellec, et al. ∙

research

∙ 07/30/2019

Local Inference in Additive Models with Decorrelated Local Linear Estimator

Additive models, as a natural generalization of linear regression, have ...

0 Zijian Guo, et al. ∙

research

∙ 05/30/2019

Limit distribution theory for multiple isotonic regression

We study limit distributions for the tuning-free max-min block estimator...

0 Qiyang Han, et al. ∙

research

∙ 05/18/2019

Factor Models for High-Dimensional Tensor Time Series

Large tensor (multi-dimensional array) data are now routinely collected ...

0 Rong Chen, et al. ∙

research

∙ 04/29/2019

Extreme Nonlinear Correlation for Multiple Random Variables and Stochastic Processes with Applications to Additive Models

The maximum correlation of functions of a pair of random variables is an...

0 Zijian Guo, et al. ∙

research

∙ 02/24/2019

De-Biasing The Lasso With Degrees-of-Freedom Adjustment

This paper studies schemes to de-bias the Lasso in sparse linear regress...

0 Pierre C. Bellec, et al. ∙

research

∙ 12/21/2018

Isotonic Regression in Multi-Dimensional Spaces and Graphs

In this paper we study minimax and adaptation rates in general isotonic ...

0 Hang Deng, et al. ∙

research

∙ 11/09/2018

Second order Stein: SURE for SURE and other applications in high-dimensional inference

Stein's formula states that a random variable of the form z^ f(z) - div ...

0 Pierre C. Bellec, et al. ∙

research

∙ 12/28/2017

Sorted Concave Penalized Regression

The Lasso is biased. Concave penalized least squares estimation (PLSE) t...

0 Long Feng, et al. ∙

research

∙ 11/14/2017

Statistically Optimal and Computationally Efficient Low Rank Tensor Completion from Noisy Entries

In this article, we develop methods for estimating a low rank tensor fro...

0 Dong Xia, et al. ∙

research

∙ 06/10/2016

Incoherent Tensor Norms and Their Applications in Higher Order Tensor Completion

In this paper, we investigate the sample size requirement for a general ...

0 Ming Yuan, et al. ∙

research

∙ 05/07/2014

On Tensor Completion via Nuclear Norm Minimization

Many problems can be formulated as recovering a low-rank tensor. Althoug...

0 Ming Yuan, et al. ∙

research

∙ 09/24/2013

Asymptotic normality and optimalities in estimation of large Gaussian graphical models

The Gaussian graphical model, a popular paradigm for studying relationsh...

0 Zhao Ren, et al. ∙

research

∙ 02/04/2013

Exact Sparse Recovery with L0 Projections

Many applications concern sparse signals, for example, detecting anomali...

0 Ping Li, et al. ∙

research

∙ 11/09/2012

Calibrated Elastic Regularization in Matrix Completion

This paper concerns the problem of matrix completion, which is to estima...

0 Tingni Sun, et al. ∙

research

∙ 08/06/2012

One Permutation Hashing for Efficient Search and Learning

Recently, the method of b-bit minwise hashing has been applied to large-...

0 Ping Li, et al. ∙

research

∙ 04/29/2012

Optimality of Graphlet Screening in High Dimensional Variable Selection

Consider a linear regression model where the design matrix X has n rows ...

0 Jiashun Jin, et al. ∙

research

∙ 02/13/2012

Sparse Matrix Inversion with Scaled Lasso

We propose a new method of learning a sparse nonnegative-definite target...

0 Tingni Sun, et al. ∙

research

∙ 01/16/2012

A General Framework of Dual Certificate Analysis for Structured Sparse Recovery Problems

This paper develops a general theoretical framework to analyze structure...

0 Cun-Hui Zhang, et al. ∙

research

∙ 12/29/2011

Estimation And Selection Via Absolute Penalized Convex Minimization And Its Multistage Adaptive Applications

The ℓ_1-penalized method, or the Lasso, has emerged as an important tool...

0 Jian Huang, et al. ∙

research

∙ 08/25/2011

A General Theory of Concave Regularization for High Dimensional Sparse Estimation Problems

Concave regularization methods provide natural procedures for sparse rec...

0 Cun-Hui Zhang, et al. ∙

research

∙ 04/24/2011

Scaled Sparse Linear Regression

Scaled sparse linear regression jointly estimates the regression coeffic...

0 Tingni Sun, et al. ∙

Cun-Hui Zhang

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