64 citations · 279 across the 30 of their papers we have counts for
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Semismooth Newton-type method for bilevel optimization: Global convergence and extensive numerical experiments
Andreas Fischer, Alain B. Zemkoho, Shenglong Zhou
We consider the standard optimistic bilevel optimization problem, in particular upper- and lower-level constraints can be coupled. By means of the lower-level value function, the p…
Support Vector Machine Classifier via Soft-Margin Loss
Huajun Wang, Yuanhai Shao, Shenglong Zhou +2
Support vector machine (SVM) has attracted great attentions for the last two decades due to its extensive applications, and thus numerous optimization models have been proposed. To…
An Extended Newton-type Algorithm for -Regularized Sparse Logistic Regression and Its Efficiency for Classifying Large-scale Datasets
Rui Wang, Naihua Xiu, Shenglong Zhou
Sparse logistic regression, as an effective tool of classification, has been developed tremendously in recent two decades, from its origination the -regularized version to…
Global and Quadratic Convergence of Newton Hard-Thresholding Pursuit
Shenglong Zhou, Naihua Xiu, Hou-Duo Qi
Algorithms based on the hard thresholding principle have been well studied with sounding theoretical guarantees in the compressed sensing and more general sparsity-constrained opti…