116 citations · 295 across the 19 of their papers we have counts for
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Dual Representation Learning for One-Step Clustering of Multi-View Data
Wei Zhang, Zhaohong Deng, Kup-Sze Choi +2
Multi-view data are commonly encountered in data mining applications. Effective extraction of information from multi-view data requires specific design of clustering methods to cat…
TSK Fuzzy System Towards Few Labeled Incomplete Multi-View Data Classification
Wei Zhang, Zhaohong Deng, Qiongdan Lou +3
Data collected by multiple methods or from multiple sources is called multi-view data. To make full use of the multi-view data, multi-view learning plays an increasingly important…
Double-Coupling Learning for Multi-Task Data Stream Classification
Yingzhong Shi, Zhaohong Deng, Haoran Chen +2
Data stream classification methods demonstrate promising performance on a single data stream by exploring the cohesion in the data stream. However, multiple data streams that invol…
Multi-View Fuzzy Clustering with The Alternative Learning between Shared Hidden Space and Partition
Zhaohong Deng, Chen Cui, Peng Xu +4
As the multi-view data grows in the real world, multi-view clus-tering has become a prominent technique in data mining, pattern recognition, and machine learning. How to exploit th…
Multi-view Clustering with the Cooperation of Visible and Hidden Views
Zhaohong Deng, Ruixiu Liu, Te Zhang +4
Multi-view data are becoming common in real-world modeling tasks and many multi-view data clustering algorithms have thus been proposed. The existing algorithms usually focus on th…
Multi-view Information-theoretic Co-clustering for Co-occurrence Data
Peng Xu, Zhaohong Deng, Kup-Sze Choi +2
Multi-view clustering has received much attention recently. Most of the existing multi-view clustering methods only focus on one-sided clustering. As the co-occurring data elements…
Joint Information Preservation for Heterogeneous Domain Adaptation
Peng Xu, Zhaohong Deng, Kup-Sze Choi +2
Domain adaptation aims to assist the modeling tasks of the target domain with knowledge of the source domain. The two domains often lie in different feature spaces due to diverse d…
Concise Fuzzy System Modeling Integrating Soft Subspace Clustering and Sparse Learning
Peng Xu, Zhaohong Deng, Chen Cui +5
The superior interpretability and uncertainty modeling ability of Takagi-Sugeno-Kang fuzzy system (TSK FS) make it possible to describe complex nonlinear systems intuitively and ef…
Transfer Representation Learning with TSK Fuzzy System
Peng Xu, Zhaohong Deng, Jun Wang +2
Transfer learning can address the learning tasks of unlabeled data in the target domain by leveraging plenty of labeled data from a different but related source domain. A core issu…
Transfer Prototype-based Fuzzy Clustering
Zhaohong Deng, Yizhang Jiang, Fu-Lai Chung +3
The traditional prototype based clustering methods, such as the well-known fuzzy c-mean (FCM) algorithm, usually need sufficient data to find a good clustering partition. If the av…
A Survey on Soft Subspace Clustering
Zhaohong Deng, Kup-Sze Choi, Yizhang Jiang +2
Subspace clustering (SC) is a promising clustering technology to identify clusters based on their associations with subspaces in high dimensional spaces. SC can be classified into…