6 citations · 20 across the 27 of their papers we have counts for
5 papers · 1 filter
Bilevel Models for Adversarial Learning and A Case Study
Yutong Zheng, Qingna Li
Adversarial learning has been attracting more and more attention thanks to the fast development of machine learning and artificial intelligence. However, due to the complicated str…
An Efficient Method for Sample Adversarial Perturbations against Nonlinear Support Vector Machines
Wen Su, Qingna Li
Adversarial perturbations have drawn great attentions in various machine learning models. In this paper, we investigate the sample adversarial perturbations for nonlinear support v…
Optimization Models and Interpretations for Three Types of Adversarial Perturbations against Support Vector Machines
Wen Su, Qingna Li, Chunfeng Cui
Adversarial perturbations have drawn great attentions in various deep neural networks. Most of them are computed by iterations and cannot be interpreted very well. In contrast, lit…
A Semismooth-Newton's-Method-Based Linearization and Approximation Approach for Kernel Support Vector Machines
Chen Jiang, Qingna Li
Support Vector Machines (SVMs) are among the most popular and the best performing classification algorithms. Various approaches have been proposed to reduce the high computation an…
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…