Representation learning in multi-view clustering: A literature review
Multi-view clustering (MVC) has attracted more and more attention in the recent few years by
making full use of complementary and consensus information between multiple views to …
making full use of complementary and consensus information between multiple views to …
Fast parameter-free multi-view subspace clustering with consensus anchor guidance
Multi-view subspace clustering has attracted intensive attention to effectively fuse multi-view
information by exploring appropriate graph structures. Although existing works have made …
information by exploring appropriate graph structures. Although existing works have made …
Robust multi-view non-negative matrix factorization with adaptive graph and diversity constraints
Multi-view clustering (MVC) has received extensive attention due to its efficient processing of
high-dimensional data. Most of the existing multi-view clustering methods are based on non …
high-dimensional data. Most of the existing multi-view clustering methods are based on non …
Robust multi-view clustering with noisy correspondence
Deep multi-view clustering leverages deep neural networks to achieve promising
performance, but almost all existing methods implicitly assume that all views are aligned …
performance, but almost all existing methods implicitly assume that all views are aligned …
Let the data choose: Flexible and diverse anchor graph fusion for scalable multi-view clustering
In the past few years, numerous multi-view graph clustering algorithms have been proposed
to enhance the clustering performance by exploring information from multiple views. Despite …
to enhance the clustering performance by exploring information from multiple views. Despite …
Masked graph learning with recurrent alignment for multimodal emotion recognition in conversation
Since Multimodal Emotion Recognition in Conversation (MERC) can be applied to public
opinion monitoring, intelligent dialogue robots, and other fields, it has received extensive …
opinion monitoring, intelligent dialogue robots, and other fields, it has received extensive …
Deep safe multi-view clustering: Reducing the risk of clustering performance degradation caused by view increase
Multi-view clustering has been shown to boost clustering performance by effectively mining
the complementary information from multiple views. However, we observe that learning from …
the complementary information from multiple views. However, we observe that learning from …
Centric graph regularized log-norm sparse non-negative matrix factorization for multi-view clustering
Multi-view non-negative matrix factorization (NMF) provides a reliable method to analyze
multiple views of data for low-dimensional representation. A variety of multi-view learning …
multiple views of data for low-dimensional representation. A variety of multi-view learning …
Breaking down multi-view clustering: a comprehensive review of multi-view approaches for complex data structures
Abstract Multi-View Clustering (MVC) is an emerging research area aiming to cluster
multiple views of the same data, which has recently drawn substantial attention. Various …
multiple views of the same data, which has recently drawn substantial attention. Various …
Self-taught multi-view spectral clustering
By integrating multiple views, ie, multi-view learning (ML), we can discover the underlying
data structures so that the performance of learning tasks can improve. As a basic and …
data structures so that the performance of learning tasks can improve. As a basic and …