activity
20192021
most citedAnomalyDAE: Dual autoencoder for anomaly detection on attributed networks

12 citations · 14 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG20212 cited

Deep Dual Support Vector Data Description for Anomaly Detection on Attributed Networks

Fengbin Zhang, Haoyi Fan, Ruidong Wang +2

Networks are ubiquitous in the real world such as social networks and communication networks, and anomaly detection on networks aims at finding nodes whose structural or attributed…

cs.LG202012 cited

AnomalyDAE: Dual autoencoder for anomaly detection on attributed networks

Haoyi Fan, Fengbin Zhang, Zuoyong Li

Anomaly detection on attributed networks aims at finding nodes whose patterns deviate significantly from the majority of reference nodes, which is pervasive in many applications su…

cs.LG2020

Correlation-aware Deep Generative Model for Unsupervised Anomaly Detection

Haoyi Fan, Fengbin Zhang, Ruidong Wang +2

Unsupervised anomaly detection aims to identify anomalous samples from highly complex and unstructured data, which is pervasive in both fundamental research and industrial applicat…

cs.CV2019

Robust Classification with Sparse Representation Fusion on Diverse Data Subsets

Chun-Mei Feng, Yong Xu, Zuoyong Li +1

Sparse Representation (SR) techniques encode the test samples into a sparse linear combination of all training samples and then classify the test samples into the class with the mi…

cs.CV2019

Joint Learning of Self-Representation and Indicator for Multi-View Image Clustering

Songsong Wu, Zhiqiang Lu, Hao Tang +4

Multi-view subspace clustering aims to divide a set of multisource data into several groups according to their underlying subspace structure. Although the spectral clustering based…