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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 …
A survey and an empirical evaluation of multi-view clustering approaches
Multi-view clustering (MVC) holds a significant role in domains like machine learning, data
mining, and pattern recognition. Despite the development of numerous new MVC …
mining, and pattern recognition. Despite the development of numerous new MVC …
Simple contrastive graph clustering
Contrastive learning has recently attracted plenty of attention in deep graph clustering due to
its promising performance. However, complicated data augmentations and time-consuming …
its promising performance. However, complicated data augmentations and time-consuming …
Low-rank tensor regularized graph fuzzy learning for multi-view data processing
Multi-view data processing is an effective tool to differentiate the levels of consumers on
electronics. Recently, the graph based multi-view clustering methods have attracted …
electronics. Recently, the graph based multi-view clustering methods have attracted …
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 …
Joint contrastive triple-learning for deep multi-view clustering
Deep multi-view clustering (MVC) is to mine and employ the complex relationships among
views to learn the compact data clusters with deep neural networks in an unsupervised …
views to learn the compact data clusters with deep neural networks in an unsupervised …
Dual contrast-driven deep multi-view clustering
Consensus representation learning is one of the most popular approaches in the field of
multi-view clustering. However, most of the existing methods cannot learn discriminative …
multi-view clustering. However, most of the existing methods cannot learn discriminative …
Multi-scale locality preserving projection for partial multi-view incomplete multi-label learning
Amidst advancements in feature extraction techniques, research on multi-view multi-label
classifications has attracted widespread interest in recent years. However, real-world …
classifications has attracted widespread interest in recent years. However, real-world …
Homophily-related: Adaptive hybrid graph filter for multi-view graph clustering
Recently there is a growing focus on graph data, and multi-view graph clustering has
become a popular area of research interest. Most of the existing methods are only …
become a popular area of research interest. Most of the existing methods are only …
Upper bounding barlow twins: A novel filter for multi-relational clustering
Multi-relational clustering is a challenging task due to the fact that diverse semantic
information conveyed in multi-layer graphs is difficult to extract and fuse. Recent methods …
information conveyed in multi-layer graphs is difficult to extract and fuse. Recent methods …