6 citations · 22 across the 32 of their papers we have counts for
Showing 2019Show all
3 papers · 1 filter
math.OC2019★ 2 cited
An Efficient Augmented Lagrangian Method for Support Vector Machine
Yinqiao Yan, Qingna Li
Support vector machine (SVM) has proved to be a successful approach for machine learning. Two typical SVM models are the L1-loss model for support vector classification (SVC) and $…
math.OC2019
A Semismooth Newton Method for Support Vector Classification and Regression
Juan Yin, Qingna Li
Support vector machine is an important and fundamental technique in machine learning. In this paper, we apply a semismooth Newton method to solve two typical SVM models: the L2-los…
cs.LG2019★ 3 cited
Ordinal Distance Metric Learning with MDS for Image Ranking
Panpan Yu, Qingna Li
Image ranking is to rank images based on some known ranked images. In this paper, we propose an improved linear ordinal distance metric learning approach based on the linear distan…