research
∙
03/29/2023
Randomly Projected Convex Clustering Model: Motivation, Realization, and Cluster Recovery Guarantees
In this paper, we propose a randomly projected convex clustering model f...
share
research
∙
12/03/2022
Beyond ADMM: A Unified Client-variance-reduced Adaptive Federated Learning Framework
As a novel distributed learning paradigm, federated learning (FL) faces ...
research
∙
06/25/2021
MARS: A second-order reduction algorithm for high-dimensional sparse precision matrices estimation
Estimation of the precision matrix (or inverse covariance matrix) is of ...
research
∙
10/22/2020
Learning Graph Laplacian with MCP
Motivated by the observation that the ability of the â„“_1 norm in promoti...
research
∙
04/17/2020
Estimation of sparse Gaussian graphical models with hidden clustering structure
Estimation of Gaussian graphical models is important in natural science ...
research
∙
02/26/2020
Efficient algorithms for multivariate shape-constrained convex regression problems
Shape-constrained convex regression problem deals with fitting a convex ...
research
∙
03/27/2019
A sparse semismooth Newton based proximal majorization-minimization algorithm for nonconvex square-root-loss regression problems
In this paper, we consider high-dimensional nonconvex square-root-loss r...
research
∙
02/01/2019
On the Closed-form Proximal Mapping and Efficient Algorithms for Exclusive Lasso Models
The exclusive lasso regularization based on the â„“_1,2 norm has become po...
research
∙
10/04/2018
Convex Clustering: Model, Theoretical Guarantee and Efficient Algorithm
Clustering is a fundamental problem in unsupervised learning. Popular me...
research
∙
09/12/2018
A Fast Globally Linearly Convergent Algorithm for the Computation of Wasserstein Barycenters
In this paper, we consider the problem of computing a Wasserstein baryce...
research
∙
08/22/2018
Efficient sparse Hessian based algorithms for the clustered lasso problem
We focus on solving the clustered lasso problem, which is a least square...
research
∙
02/20/2018
An Efficient Semismooth Newton Based Algorithm for Convex Clustering
Clustering may be the most fundamental problem in unsupervised learning ...
research
∙
10/13/2012
