7 citations · 26 across the 13 of their papers we have counts for
29 papers
Solving Challenging Large Scale QAPs
Koichi Fujii, Naoki Ito, Sunyoung Kim +3
We report our progress on the project for solving larger scale quadratic assignment problems (QAPs). Our main approach to solve large scale NP-hard combinatorial optimization probl…
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…
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…
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…
Mesh Independence of a Majorized ABCD Method for Sparse PDE-constrained Optimization Problems
Xiaoliang Song, Defeng Sun, Kim-Chuan Toh
A majorized accelerated block coordinate descent (mABCD) method in Hilbert space is analyzed to solve a sparse PDE-constrained optimization problem via its dual. The finite element…
A Proximal Point Dual Newton Algorithm for Solving Group Graphical Lasso Problems
Yangjing Zhang, Ning Zhang, Defeng Sun +1
Undirected graphical models have been especially popular for learning the conditional independence structure among a large number of variables where the observations are drawn inde…