research
∙
08/15/2023
Classification of Data Generated by Gaussian Mixture Models Using Deep ReLU Networks
This paper studies the binary classification of unbounded data from ℝ^d ...
share
research
∙
07/11/2023
Conformalization of Sparse Generalized Linear Models
Given a sequence of observable variables {(x_1, y_1), …, (x_n, y_n)}, th...
research
∙
05/30/2023
Generalization Bounds for Magnitude-Based Pruning via Sparse Matrix Sketching
In this paper, we derive a novel bound on the generalization error of Ma...
research
∙
03/27/2023
Adjusted Wasserstein Distributionally Robust Estimator in Statistical Learning
We propose an adjusted Wasserstein distributionally robust estimator – b...
research
∙
03/07/2023
A Survey of Numerical Algorithms that can Solve the Lasso Problems
In statistics, the least absolute shrinkage and selection operator (Lass...
research
∙
01/23/2023
Improved Rate of First Order Algorithms for Entropic Optimal Transport
This paper improves the state-of-the-art rate of a first-order algorithm...
research
∙
12/02/2022
Covariance Estimators for the ROOT-SGD Algorithm in Online Learning
Online learning naturally arises in many statistical and machine learnin...
research
∙
10/29/2022
Solving a Special Type of Optimal Transport Problem by a Modified Hungarian Algorithm
We observe that computing empirical Wasserstein distance in the independ...
research
∙
10/25/2022
Learning Ability of Interpolating Convolutional Neural Networks
It is frequently observed that overparameterized neural networks general...
research
∙
05/20/2022
Hot-spots Detection in Count Data by Poisson Assisted Smooth Sparse Tensor Decomposition
Count data occur widely in many bio-surveillance and healthcare applicat...
research
∙
04/29/2022
The Directional Bias Helps Stochastic Gradient Descent to Generalize in Kernel Regression Models
We study the Stochastic Gradient Descent (SGD) algorithm in nonparametri...
research
∙
04/29/2022
Implicit Regularization Properties of Variance Reduced Stochastic Mirror Descent
In machine learning and statistical data analysis, we often run into obj...
research
∙
03/02/2022
An Accelerated Stochastic Algorithm for Solving the Optimal Transport Problem
We propose a novel accelerated stochastic algorithm – primal-dual accele...
research
∙
03/18/2021
Identification of Underlying Dynamic System from Noisy Data with Splines
In this paper, we propose a two-stage method called Spline Assisted Part...
research
∙
03/12/2021
Asymptotic Theory of ℓ_1-Regularized PDE Identification from a Single Noisy Trajectory
We prove the support recovery for a general class of linear and nonlinea...
research
∙
10/26/2020
A Homotopic Method to Solve the Lasso Problems with an Improved Upper Bound of Convergence Rate
In optimization, it is known that when the objective functions are stric...
research
∙
09/19/2020
Fast and Asymptotically Powerful Detection for Filamentary Objects in Digital Images
Given an inhomogeneous chain embedded in a noisy image, we consider the ...
research
∙
12/31/2019
Asymptotic convergence rate of the longest run in an inflating Bernoulli net
In image detection, one problem is to test whether the set, though mostl...
research
∙
12/02/2019
Factor Analysis on Citation, Using a Combined Latent and Logistic Regression Model
We propose a combined model, which integrates the latent factor model an...
research
∙
11/09/2019
Optimal Shape Control via L_∞ Loss for Composite Fuselage Assembly
Shape control is critical to ensure the quality of composite fuselage as...
research
∙
11/07/2019
Optimal Projections in the Distance-Based Statistical Methods
This paper introduces a new way to calculate distance-based statistics, ...
research
∙
02/28/2019
Distance-Based Independence Screening for Canonical Analysis
This paper introduces a new method named Distance-based Independence Scr...
research
∙
12/18/2018
A Unifying Framework of High-Dimensional Sparse Estimation with Difference-of-Convex (DC) Regularizations
Under the linear regression framework, we study the variable selection p...
research
∙
11/04/2015
