Multi-view clustering: A survey
Y Yang, H Wang - Big data mining and analytics, 2018 - ieeexplore.ieee.org
In the big data era, the data are generated from different sources or observed from different
views. These data are referred to as multi-view data. Unleashing the power of knowledge in …
views. These data are referred to as multi-view data. Unleashing the power of knowledge in …
Kernel-based weighted multi-view clustering
G Tzortzis, A Likas - … IEEE 12th international conference on data …, 2012 - ieeexplore.ieee.org
Exploiting multiple representations, or views, for the same set of instances within a clustering
framework is a popular practice for boosting clustering accuracy. However, some of the …
framework is a popular practice for boosting clustering accuracy. However, some of the …
Improved normalized cut for multi-view clustering
Spectral clustering (SC) algorithms have been successful in discovering meaningful patterns
since they can group arbitrarily shaped data structures. Traditional SC approaches typically …
since they can group arbitrarily shaped data structures. Traditional SC approaches typically …
Feature concatenation multi-view subspace clustering
Multi-view clustering is a learning paradigm based on multi-view data. Since statistic
properties of different views are diverse, even incompatible, few approaches implement …
properties of different views are diverse, even incompatible, few approaches implement …
Multi-View K-Means with Laplacian Embedding
Most of the existing multi-view clustering algorithms are performed in the original feature
space, and their performance in heavily reliant on the quality of the raw data. Besides, some …
space, and their performance in heavily reliant on the quality of the raw data. Besides, some …
Adaptive Topological Graph Learning for Generalized Multi-View Clustering
W He, Z Zhang - 2023 International Joint Conference on Neural …, 2023 - ieeexplore.ieee.org
Graph-based multi-view clustering methods construct affinity graphs to depict the potential
cluster structure in given data and further partition them into respective groups without the …
cluster structure in given data and further partition them into respective groups without the …
Multi-view clustering via neighbor domain correlation learning
With the development of data science, more and more data are presented in the form of multi-
view. Compared with single-view feature learning, multi-view feature learning is more …
view. Compared with single-view feature learning, multi-view feature learning is more …
Anchor-based incomplete multi-view spectral clustering
In the past decade, multi-view clustering has become a research hot spot of machine
learning. In traditional multi-view clustering methods, all views of the data points are …
learning. In traditional multi-view clustering methods, all views of the data points are …
Generalized incomplete multiview clustering with flexible locality structure diffusion
An important underlying assumption that guides the success of the existing multiview
learning algorithms is the full observation of the multiview data. However, such rigorous …
learning algorithms is the full observation of the multiview data. However, such rigorous …
Kappa based weighted multi-view clustering with feature selection
C Zhu - Proceedings of the 2018 International Conference on …, 2018 - dl.acm.org
In recent years, multi-view clustering has been developed to a high level and widely used in
many real-world applications. Since different views are variable representations of the same …
many real-world applications. Since different views are variable representations of the same …