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07/14/2023
Adaptive Linear Estimating Equations
Sequential data collection has emerged as a widely adopted technique for...
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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, ...
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10/29/2021
CP Factor Model for Dynamic Tensors
Observations in various applications are frequently represented as a tim...
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08/10/2021
Tensor Principal Component Analysis in High Dimensional CP Models
The CP decomposition for high dimensional non-orthogonal spike tensors i...
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07/08/2021
Asymptotic normality of robust M-estimators with convex penalty
This paper develops asymptotic normality results for individual coordina...
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03/17/2021
Simultaneous Decorrelation of Matrix Time Series
We propose a contemporaneous bilinear transformation for matrix time ser...
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11/13/2020
Rank Determination in Tensor Factor Model
Factor model is an appealing and effective analytic tool for high-dimens...
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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...
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06/04/2020
Tensor Factor Model Estimation by Iterative Projection
Tensor time series, which is a time series consisting of tensorial obser...
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01/20/2020
Confidence intervals for multiple isotonic regression and other monotone models
We consider the problem of constructing pointwise confidence intervals i...
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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...
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07/30/2019
Local Inference in Additive Models with Decorrelated Local Linear Estimator
Additive models, as a natural generalization of linear regression, have ...
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05/30/2019
Limit distribution theory for multiple isotonic regression
We study limit distributions for the tuning-free max-min block estimator...
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05/18/2019
Factor Models for High-Dimensional Tensor Time Series
Large tensor (multi-dimensional array) data are now routinely collected ...
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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...
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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...
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12/21/2018
Isotonic Regression in Multi-Dimensional Spaces and Graphs
In this paper we study minimax and adaptation rates in general isotonic ...
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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 ...
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12/28/2017
Sorted Concave Penalized Regression
The Lasso is biased. Concave penalized least squares estimation (PLSE) t...
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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...
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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 ...
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05/07/2014
On Tensor Completion via Nuclear Norm Minimization
Many problems can be formulated as recovering a low-rank tensor. Althoug...
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09/24/2013
Asymptotic normality and optimalities in estimation of large Gaussian graphical models
The Gaussian graphical model, a popular paradigm for studying relationsh...
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02/04/2013
Exact Sparse Recovery with L0 Projections
Many applications concern sparse signals, for example, detecting anomali...
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11/09/2012
Calibrated Elastic Regularization in Matrix Completion
This paper concerns the problem of matrix completion, which is to estima...
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08/06/2012
One Permutation Hashing for Efficient Search and Learning
Recently, the method of b-bit minwise hashing has been applied to large-...
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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 ...
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02/13/2012
Sparse Matrix Inversion with Scaled Lasso
We propose a new method of learning a sparse nonnegative-definite target...
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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...
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12/29/2011
Estimation And Selection Via Absolute Penalized Convex Minimization And Its Multistage Adaptive Applications
The â„“_1-penalized method, or the Lasso, has emerged as an important tool...
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08/25/2011
A General Theory of Concave Regularization for High Dimensional Sparse Estimation Problems
Concave regularization methods provide natural procedures for sparse rec...
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04/24/2011