most citedEvaluating the Robustness of Nearest Neighbor Classifiers: A Primal-Dual Perspective

13 citations · 28 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2019

Sample Adaptive Multiple Kernel Learning for Failure Prediction of Railway Points

Zhibin Li, Jian Zhang, Qiang Wu +3

Railway points are among the key components of railway infrastructure. As a part of signal equipment, points control the routes of trains at railway junctions, having a significant…

cs.CV2019

Defending Against Adversarial Attacks Using Random Forests

Yifan Ding, Liqiang Wang, Huan Zhang +3

As deep neural networks (DNNs) have become increasingly important and popular, the robustness of DNNs is the key to the safety of both the Internet and the physical world. Unfortun…

cs.LG20194 cited

Joint Semantic Domain Alignment and Target Classifier Learning for Unsupervised Domain Adaptation

Dong-Dong Chen, Yisen Wang, Jinfeng Yi +2

Unsupervised domain adaptation aims to transfer the classifier learned from the source domain to the target domain in an unsupervised manner. With the help of target pseudo-labels,…

cs.LG201913 cited

Evaluating the Robustness of Nearest Neighbor Classifiers: A Primal-Dual Perspective

Lu Wang, Xuanqing Liu, Jinfeng Yi +2

We study the problem of computing the minimum adversarial perturbation of the Nearest Neighbor (NN) classifiers. Previous attempts either conduct attacks on continuous approximatio…

cs.LG201911 cited

Improving the Robustness of Deep Neural Networks via Adversarial Training with Triplet Loss

Pengcheng Li, Jinfeng Yi, Bowen Zhou +1

Recent studies have highlighted that deep neural networks (DNNs) are vulnerable to adversarial examples. In this paper, we improve the robustness of DNNs by utilizing techniques of…

cs.CV2019

Inferring the Importance of Product Appearance: A Step Towards the Screenless Revolution

Yongshun Gong, Jinfeng Yi, Dongdong Chen +3

Nowadays, almost all the online orders were placed through screened devices such as mobile phones, tablets, and computers. With the rapid development of the Internet of Things (IoT…