research
∙
04/29/2023
Estimation and Inference for Minimizer and Minimum of Convex Functions: Optimality, Adaptivity, and Uncertainty Principles
Optimal estimation and inference for both the minimizer and minimum of a...
share
research
∙
03/13/2023
Score Attack: A Lower Bound Technique for Optimal Differentially Private Learning
Achieving optimal statistical performance while ensuring the privacy of ...
research
∙
01/25/2023
Statistical Inference and Large-scale Multiple Testing for High-dimensional Regression Models
This paper presents a selective survey of recent developments in statist...
research
∙
01/03/2023
Testing High-dimensional Multinomials with Applications to Text Analysis
Motivated by applications in text mining and discrete distribution infer...
research
∙
11/22/2022
Transfer Learning for Contextual Multi-armed Bandits
Motivated by a range of applications, we study in this paper the problem...
research
∙
03/22/2022
Locally Adaptive Transfer Learning Algorithms for Large-Scale Multiple Testing
Transfer learning has enjoyed increasing popularity in a range of big da...
research
∙
02/21/2022
Statistical Inference for Genetic Relatedness Based on High-Dimensional Logistic Regression
This paper studies the problem of statistical inference for genetic rela...
research
∙
01/17/2022
Matrix Reordering for Noisy Disordered Matrices: Optimality and Computationally Efficient Algorithms
Motivated by applications in single-cell biology and metagenomics, we co...
research
∙
01/11/2022
Estimation and Inference with Proxy Data and its Genetic Applications
Existing high-dimensional statistical methods are largely established fo...
research
∙
09/07/2021
SIHR: An R Package for Statistical Inference in High-dimensional Linear and Logistic Regression Models
We introduce and illustrate through numerical examples the R package wh...
research
∙
07/01/2021
Distributed Nonparametric Function Estimation: Optimal Rate of Convergence and Cost of Adaptation
Distributed minimax estimation and distributed adaptive estimation under...
research
∙
05/16/2021
Theoretical Foundations of t-SNE for Visualizing High-Dimensional Clustered Data
This study investigates the theoretical foundations of t-distributed sto...
research
∙
11/08/2020
The Cost of Privacy in Generalized Linear Models: Algorithms and Minimax Lower Bounds
We propose differentially private algorithms for parameter estimation in...
research
∙
11/06/2020
Estimation, Confidence Intervals, and Large-Scale Hypotheses Testing for High-Dimensional Mixed Linear Regression
This paper studies the high-dimensional mixed linear regression (MLR) wh...
research
∙
10/21/2020
Transfer Learning in Large-scale Gaussian Graphical Models with False Discovery Rate Control
Transfer learning for high-dimensional Gaussian graphical models (GGMs) ...
research
∙
08/28/2020
On the Non-Asymptotic Concentration of Heteroskedastic Wishart-type Matrix
This paper focuses on the non-asymptotic concentration of the heterosked...
research
∙
06/18/2020
Transfer Learning for High-dimensional Linear Regression: Prediction, Estimation, and Minimax Optimality
This paper considers the estimation and prediction of a high-dimensional...
research
∙
06/02/2020
Two Robust Tools for Inference about Causal Effects with Invalid Instruments
Instrumental variables have been widely used to estimate the causal effe...
research
∙
02/18/2020
Optimal Structured Principal Subspace Estimation: Metric Entropy and Minimax Rates
Driven by a wide range of applications, many principal subspace estimati...
research
∙
01/24/2020
Distributed Gaussian Mean Estimation under Communication Constraints: Optimal Rates and Communication-Efficient Algorithms
We study distributed estimation of a Gaussian mean under communication c...
research
∙
12/05/2019
A Convex Optimization Approach to High-Dimensional Sparse Quadratic Discriminant Analysis
In this paper, we study high-dimensional sparse Quadratic Discriminant A...
research
∙
11/28/2019
Optimal and Adaptive Estimation of Extreme Values in the Permuted Monotone Matrix Model
Motivated by applications in metagenomics, we consider the permuted mono...
research
∙
11/26/2019
High Dimensional M-Estimation with Missing Outcomes: A Semi-Parametric Framework
We consider high dimensional M-estimation in settings where the response...
research
∙
11/24/2019
Optimal Permutation Recovery in Permuted Monotone Matrix Model
Motivated by recent research on quantifying bacterial growth dynamics ba...
research
∙
09/21/2019
Sparse Group Lasso: Optimal Sample Complexity, Convergence Rate, and Statistical Inference
In this paper, we study sparse group Lasso for high-dimensional double s...
research
∙
09/04/2019
Group Inference in High Dimensions with Applications to Hierarchical Testing
Group inference has been a long-standing question in statistics and the ...
research
∙
06/07/2019
Transfer Learning for Nonparametric Classification: Minimax Rate and Adaptive Classifier
Human learners have the natural ability to use knowledge gained in one s...
research
∙
05/21/2019
Asymptotic Analysis for Extreme Eigenvalues of Principal Minors of Random Matrices
Consider a standard white Wishart matrix with parameters n and p. Motiva...
research
∙
02/12/2019
The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy
Privacy-preserving data analysis is a rising challenge in contemporary s...
research
∙
10/19/2018
Heteroskedastic PCA: Algorithm, Optimality, and Applications
Principal component analysis (PCA) and singular value decomposition (SVD...
research
∙
06/16/2018
Semi-supervised Inference for Explained Variance in High-dimensional Linear Regression and Its Applications
We consider statistical inference for the explained variance β^Σβ under ...
research
∙
05/17/2018
Global and Simultaneous Hypothesis Testing for High-Dimensional Logistic Regression Models
High-dimensional logistic regression is widely used in analyzing data wi...
research
∙
04/09/2018
High-dimensional Linear Discriminant Analysis: Optimality, Adaptive Algorithm, and Missing Data
This paper aims to develop an optimality theory for linear discriminant ...
research
∙
01/24/2018
Optimal Estimation of Simultaneous Signals Using Absolute Inner Product with Applications to Integrative Genomics
Integrating the summary statistics from genome-wide association study (G...
research
∙
01/01/2018
Statistical and Computational Limits for Sparse Matrix Detection
This paper investigates the fundamental limits for detecting a high-dime...
research
∙
09/12/2017
Weighted Message Passing and Minimum Energy Flow for Heterogeneous Stochastic Block Models with Side Information
We study the misclassification error for community detection in general ...
research
∙
06/23/2016
Semi-supervised Inference: General Theory and Estimation of Means
We propose a general semi-supervised inference framework focused on the ...
research
∙
03/22/2016
Inference via Message Passing on Partially Labeled Stochastic Block Models
We study the community detection and recovery problem in partially-label...
research
∙
02/16/2016
A Sparse PCA Approach to Clustering
We discuss a clustering method for Gaussian mixture model based on the s...
research
∙
06/10/2015
Optimal Rates of Convergence for Noisy Sparse Phase Retrieval via Thresholded Wirtinger Flow
This paper considers the noisy sparse phase retrieval problem: recoverin...
research
∙
04/08/2015
Structured Matrix Completion with Applications to Genomic Data Integration
Matrix completion has attracted significant recent attention in many fie...
research
∙
02/06/2015
Computational and Statistical Boundaries for Submatrix Localization in a Large Noisy Matrix
The interplay between computational efficiency and statistical accuracy ...
research
∙
07/10/2014
Rate-Optimal Detection of Very Short Signal Segments
Motivated by a range of applications in engineering and genomics, we con...
research
∙
04/23/2014
Robust and computationally feasible community detection in the presence of arbitrary outlier nodes
Community detection, which aims to cluster N nodes in a given graph into...
research
∙
04/17/2014
Geometric Inference for General High-Dimensional Linear Inverse Problems
This paper presents a unified geometric framework for the statistical an...
research
∙
09/24/2013
A Max-Norm Constrained Minimization Approach to 1-Bit Matrix Completion
We consider in this paper the problem of noisy 1-bit matrix completion u...
research
∙
06/05/2013
Sparse Representation of a Polytope and Recovery of Sparse Signals and Low-rank Matrices
This paper considers compressed sensing and affine rank minimization in ...
research
∙
03/02/2013