455 citations · 2.1k across the 25 of their papers we have counts for
11 papers · 1 filter
Efficient Multi-view Clustering via Unified and Discrete Bipartite Graph Learning
Si-Guo Fang, Dong Huang, Xiao-Sha Cai +3
Although previous graph-based multi-view clustering algorithms have gained significant progress, most of them are still faced with three limitations. First, they often suffer from…
Adaptively-weighted Integral Space for Fast Multiview Clustering
Man-Sheng Chen, Tuo Liu, Chang-Dong Wang +2
Multiview clustering has been extensively studied to take advantage of multi-source information to improve the clustering performance. In general, most of the existing works typica…
Strongly Augmented Contrastive Clustering
Xiaozhi Deng, Dong Huang, Ding-Hua Chen +2
Deep clustering has attracted increasing attention in recent years due to its capability of joint representation learning and clustering via deep neural networks. In its latest dev…
Vision Transformer for Contrastive Clustering
Hua-Bao Ling, Bowen Zhu, Dong Huang +3
Vision Transformer (ViT) has shown its advantages over the convolutional neural network (CNN) with its ability to capture global long-range dependencies for visual representation l…
Deep Image Clustering with Contrastive Learning and Multi-scale Graph Convolutional Networks
Yuankun Xu, Dong Huang, Chang-Dong Wang +1
Deep clustering has shown its promising capability in joint representation learning and clustering via deep neural networks. Despite the significant progress, the existing deep clu…
Multi-party Secure Broad Learning System for Privacy Preserving
Xiao-Kai Cao, Chang-Dong Wang, Jian-Huang Lai +2
Multi-party learning is an indispensable technique for improving the learning performance via integrating data from multiple parties. Unfortunately, directly integrating multi-part…
DeepCluE: Enhanced Image Clustering via Multi-layer Ensembles in Deep Neural Networks
Dong Huang, Ding-Hua Chen, Xiangji Chen +2
Deep clustering has recently emerged as a promising technique for complex data clustering. Despite the considerable progress, previous deep clustering works mostly build or learn t…
Broad Recommender System: An Efficient Nonlinear Collaborative Filtering Approach
Ling Huang, Can-Rong Guan, Zhen-Wei Huang +4
Recently, Deep Neural Networks (DNNs) have been widely introduced into Collaborative Filtering (CF) to produce more accurate recommendation results due to their capability of captu…
Joint Multi-view Unsupervised Feature Selection and Graph Learning
Si-Guo Fang, Dong Huang, Chang-Dong Wang +1
Despite significant progress, previous multi-view unsupervised feature selection methods mostly suffer from two limitations. First, they generally utilize either cluster structure…
GSR: Global Graph Guided Session-based Recommendation
Zhi-Hong Deng, Chang-Dong Wang, Ling Huang +2
Session-based recommendation tries to make use of anonymous session data to deliver high-quality recommendation under the condition that user-profiles and the complete historical b…
Fast Multi-view Clustering via Ensembles: Towards Scalability, Superiority, and Simplicity
Dong Huang, Chang-Dong Wang, Jian-Huang Lai
Despite significant progress, there remain three limitations to the previous multi-view clustering algorithms. First, they often suffer from high computational complexity, restrict…