26 citations · 60 across the 6 of their papers we have counts for
6 papers
Progressive Cluster Purification for Unsupervised Feature Learning
Yifei Zhang, Chang Liu, Yu Zhou +3
In unsupervised feature learning, sample specificity based methods ignore the inter-class information, which deteriorates the discriminative capability of representation models. Cl…
Automated Radiological Report Generation For Chest X-Rays With Weakly-Supervised End-to-End Deep Learning
Shuai Zhang, Xiaoyan Xin, Yang Wang +7
The chest X-Ray (CXR) is the one of the most common clinical exam used to diagnose thoracic diseases and abnormalities. The volume of CXR scans generated daily in hospitals is huge…
Adversarial Attack on Hierarchical Graph Pooling Neural Networks
Haoteng Tang, Guixiang Ma, Yurong Chen +4
Recent years have witnessed the emergence and development of graph neural networks (GNNs), which have been shown as a powerful approach for graph representation learning in many ta…
A New Ensemble Method for Concessively Targeted Multi-model Attack
Ziwen He, Wei Wang, Xinsheng Xuan +2
It is well known that deep learning models are vulnerable to adversarial examples crafted by maliciously adding perturbations to original inputs. There are two types of attacks: ta…
Scalable Fine-grained Generated Image Classification Based on Deep Metric Learning
Xinsheng Xuan, Bo Peng, Wei Wang +1
Recently, generated images could reach very high quality, even human eyes could not tell them apart from real images. Although there are already some methods for detecting generate…
Multi-View Active Learning in the Non-Realizable Case
Wei Wang, Zhi-Hua Zhou
The sample complexity of active learning under the realizability assumption has been well-studied. The realizability assumption, however, rarely holds in practice. In this paper, w…