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Multi-View Multiple Clustering [PDF]
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019 Multiple clustering aims at exploring alternative clusterings to organize the data into meaningful groups from different perspectives. Existing multiple clustering algorithms are designed for single-view data. We assume that the individuality and commonality of multi-view data can be leveraged to generate high-quality and diverse clusterings.
Shixin Yao +4 more
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Smoothed Multi-view Subspace Clustering [PDF]
, 2021 In recent years, multi-view subspace clustering has achieved impressive performance due to the exploitation of complementary imformation across multiple views. However, multi-view data can be very complicated and are not easy to cluster in real-world applications. Most existing methods operate on raw data and may not obtain the optimal solution.
Peng Chen +3 more
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Tsinghua Science and Technology, 2021 In recent years, multi-view clustering research has attracted considerable attention because of the rapidly growing demand for unsupervised analysis of multi-view data in practical applications.
Jie Hu, Yi Pan, Tianrui Li, Yan Yang
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Multi-view Hierarchical Clustering
CoRR, 2020 This paper focuses on the multi-view clustering, which aims to promote clustering results with multi-view data. Usually, most existing works suffer from the issues of parameter selection and high computational complexity. To overcome these limitations, we propose a Multi-view Hierarchical Clustering (MHC), which partitions multi-view data recursively ...
Qinghai Zheng, Jihua Zhu, Shuangxun Ma
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Multi-view Fuzzy Clustering Combining Visual and Hidden Information with Feature Weighting
Jisuanji kexue yu tansuo, 2021 Multi-view clustering is a type of multi-view learning method applied to unsupervised learning, which aims to use the feature set of different views to enhance the effect of clustering.
LIANG Ling, DENG Zhaohong, WANG Shitong
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Multi-View Fuzzy Clustering Algorithm Fused with KL Information [PDF]
Jisuanji gongcheng, 2022 Existing multi-view Fuzzy C-Means(FCM) clustering algorithms usually artificially decompose multi-view data into multiple single-view data for processing, reducing the clustering accuracy of view data and affecting the results of global data division.To ...
HE Na, MA Yingcang
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Fusing Local and Global Information for One-Step Multi-View Subspace Clustering
Applied Sciences, 2022 Multi-view subspace clustering has drawn significant attention in the pattern recognition and machine learning research community. However, most of the existing multi-view subspace clustering methods are still limited in two aspects.
Yiqiang Duan +3 more
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One-step Multi-view Clustering Based on Diversity and Consistency [PDF]
Jisuanji gongchengWith the development of data collection technology, multi-view data have become increasingly common. Compared to single-view data, multi-view data contain richer information, which is usually characterized by consistency and diversity information.
HU Aoran, CHEN Xiaohong
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Error-robust multi-view clustering [PDF]
2017 IEEE International Conference on Big Data (Big Data), 2017 In the era of big data, data may come from multiple sources, known as multi-view data. Multi-view clustering aims at generating better clusters by exploiting complementary and consistent information from multiple views rather than relying on the individual view. Due to inevitable system errors caused by data-captured sensors or others, the data in each
Mehrnaz Najafi +2 more
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A Multi-View Clustering Algorithm for Mixed Numeric and Categorical Data
IEEE Access, 2021 Clustering data with both numeric and categorical attributes is of great importance as such data are ubiquitous in real-world problems. Multi-view learning approaches have proven to be more effective and having better generalisation ability compared to ...
Jinchao Ji +5 more
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