Results 221 to 230 of about 86,218 (261)

Multi-view Subspace Clustering

2015 IEEE International Conference on Computer Vision (ICCV), 2015
For many computer vision applications, the data sets distribute on certain low-dimensional subspaces. Subspace clustering is to find such underlying subspaces and cluster the data points correctly. In this paper, we propose a novel multi-view subspace clustering method. The proposed method performs clustering on the subspace representation of each view
Hongchang Gao, Feiping Nie 0001, Xuelong Li 0001, Heng Huang 0001   +3 more
openaire   +1 more source

Multi-view clustering ensembles

2013 International Conference on Machine Learning and Cybernetics, 2013
Multi-view clustering and clustering ensembles have become increasingly popular in recent years. Multi-view clustering employs the relationship between views to cluster data; clustering ensembles combine different component clusterings to a better final partition.
Xijiong Xie, Shiliang Sun
openaire   +1 more source

Multi-view clustering with interactive mechanism

Neurocomputing, 2021
Abstract Existing multi-view clustering methods either seek to directly learn a consistent spectral embedding, or to learn a consistent graph. This work presents a novel model, called Multi-view Clustering with Interactive Mechanism (MCIM). Using the interactive mechanism, the uniform graph and spectral embedding can be learned alternatively and ...
Danyang Wu, Zhanxuan Hu, Feiping Nie 0001, Rong Wang 0001, Hui Yang 0005, Xuelong Li 0001   +5 more
openaire   +1 more source

Multi-view intact space clustering

Pattern Recognition, 2017
Multi-view clustering is a hot research topic due to the urgent need for analyzing a vast amount of heterogeneous data. Although many multi-view clustering methods have been developed, they have not addressed the view-insufficiency issue. That is, most of the existing multi-view clustering methods assume that each individual view is sufficient for ...
Ling Huang 0002, Hong-Yang Chao, Chang-Dong Wang 0001   +2 more
openaire   +1 more source

Lifelong Multi-view Spectral Clustering

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023
In recent years, spectral clustering has become a well-known and effective algorithm in machine learning. However, traditional spectral clustering algorithms are designed for single-view data and fixed task setting. This can become a limitation when dealing with new tasks in a sequence, as it requires accessing previously learned tasks.
Hecheng Cai, Yuze Tan, Shudong Huang, Jiancheng Lv 0001   +3 more
openaire   +1 more source

Partial multi-view spectral clustering

Neurocomputing, 2018
Abstract The partial multi-view clustering is an emerging hot research area. For example, in web page clustering, the web page content or its linkage information may suffer from the missing of some data. Traditional multi-view clustering methods deal with this kind of problem by completing and clustering separately and thus degrade the clustering ...
Yang Cai, Yuanyuan Jiao, Wenzhang Zhuge, Hong Tao, Chenping Hou   +4 more
openaire   +1 more source

Incremental multi-view spectral clustering

Knowledge-Based Systems, 2019
Abstract Multi-view learning has attracted increasing attention in recent years, and the existing multi-view learning methods learn a consensus result by collecting all views. These methods have two obvious limitations. First, it is not scalable; with limited computational resources it would be difficult, if not impossible, to collect and process a ...
Peng Zhou 0006, Yi-Dong Shen, Liang Du 0003, Fan Ye, Xuejun Li 0001   +4 more
openaire   +1 more source

Multi-view Clustering on Relational Data

2014
Clustering is a popular task in knowledge discovery. In this chapter we illustrate this fact with a new clustering algorithm that is able to partition objects taking into account simultaneously their relational descriptions given by multiple dissimilarity matrices.
Francisco de A. T. de Carvalho, Yves Lechevallier, Thierry Despeyroux, Filipe M. de Melo   +3 more
openaire   +1 more source

Incomplete multi-view spectral clustering

Journal of Intelligent & Fuzzy Systems, 2020
 Multi-view clustering algorithms mostly apply to data without incomplete instances. However, in real-world applications, representations for the same instance are probably absent from several but not all views. This incompleteness disables traditional multi-view clustering methods from grouping incomplete multi-view data.
Qianli Zhao, Linlin Zong, Xianchao Zhang 0001, Xinyue Liu 0002, Hong Yu 0005   +4 more
openaire   +1 more source

Multi-view Proximity Learning for Clustering

2018
In recent years, multi-view clustering has become a hot research topic due to the increasing amount of multi-view data. Among existing multi-view clustering methods, proximity-based method is a typical class and achieves much success. Usually, these methods need proximity matrices as inputs, which can be constructed by some nearest-neighbors-based ...
Kun-Yu Lin, Ling Huang 0002, Chang-Dong Wang 0001, Hong-Yang Chao   +3 more
openaire   +1 more source