activity
20182020
most citedEfficient algorithms for multivariate shape-constrained convex regression problems

7 citations · 12 across the 3 of their papers we have counts for

collaborators

5 papers

math.OC20203 cited

Adaptive Sieving with PPDNA: Generating Solution Paths of Exclusive Lasso Models

Meixia Lin, Yancheng Yuan, Defeng Sun +1

The exclusive lasso (also known as elitist lasso) regularization has become popular recently due to its superior performance on structured sparsity. Its complex nature poses diffic…

math.OC20202 cited

Estimation of sparse Gaussian graphical models with hidden clustering structure

Meixia Lin, Defeng Sun, Kim-Chuan Toh +1

Estimation of Gaussian graphical models is important in natural science when modeling the statistical relationships between variables in the form of a graph. The sparsity and clust…

math.OC20207 cited

Efficient algorithms for multivariate shape-constrained convex regression problems

Meixia Lin, Defeng Sun, Kim-Chuan Toh

Shape-constrained convex regression problem deals with fitting a convex function to the observed data, where additional constraints are imposed, such as component-wise monotonicity…

math.OC2019

A dual Newton based preconditioned proximal point algorithm for exclusive lasso models

Meixia Lin, Defeng Sun, Kim-Chuan Toh +1

The exclusive lasso (also known as elitist lasso) regularization has become popular recently due to its superior performance on group sparsity. Compared to the group lasso regulari…

cond-mat.supr-con2018

Unravelling the mechanism of the semiconducting-like behavior and its relation to superconductivity in (CaFePtAs)PtAs

Run Yang, Yaomin Dai, Jia Yu +6

The temperature-dependence of the in-plane optical properties of (CaFePtAs)PtAs have been investigated for the undoped (0) parent compound, and…