Structure-guided feature and cluster contrastive learning for multi-view clustering
Z Shu, B Li, C Mao, S Gao, Z Yu - Neurocomputing, 2024 - Elsevier
Multi-view clustering (MVC) technology performs unsupervised clustering on data collected
from multiple sources, and has received intense attention in recent years. However, most …
from multiple sources, and has received intense attention in recent years. However, most …
One-stage multi-view clustering with hierarchical attributes extraction
Multi-view clustering (MVC) has received significant attention, and obtained praiseworthy
performance improvement in comparison with signal-view clustering, since it can effectively …
performance improvement in comparison with signal-view clustering, since it can effectively …
Anchor-Sharing and Clusterwise Contrastive Network for Multiview Representation Learning
Multiview clustering (MVC) has gained significant attention as it enables the partitioning of
samples into their respective categories through unsupervised learning. However, there are …
samples into their respective categories through unsupervised learning. However, there are …
Learning consensus representations in multi-latent spaces for multi-view clustering
Multi-view clustering integrates features from different views to perform clustering. This
problem has attracted increasing attention in recent years because multi-view data has …
problem has attracted increasing attention in recent years because multi-view data has …
Learning Cluster-Wise Anchors for Multi-View Clustering
Due to its effectiveness and efficiency, anchor based multi-view clustering (MVC) has
recently attracted much attention. Most existing approaches try to adaptively learn anchors to …
recently attracted much attention. Most existing approaches try to adaptively learn anchors to …
Neighbor-aware deep multi-view clustering via graph convolutional network
Multi-view clustering (MVC) enhances the clustering performance of data by combining
correlation information from different views. However, most existing MVC approaches …
correlation information from different views. However, most existing MVC approaches …
Deep Multiview Clustering by Pseudo-Label Guided Contrastive Learning and Dual Correlation Learning
Deep multiview clustering (MVC) is to learn and utilize the rich relations across different
views to enhance the clustering performance under a human-designed deep network …
views to enhance the clustering performance under a human-designed deep network …
Self-supervised discriminative feature learning for deep multi-view clustering
Multi-view clustering is an important research topic due to its capability to utilize
complementary information from multiple views. However, there are few methods to consider …
complementary information from multiple views. However, there are few methods to consider …
Scalable and parameter-free fusion graph learning for multi-view clustering
Multi-view clustering aims to capture the consistency and complementary information
present in view-specific data to achieve clustering alignment. However, existing multi-view …
present in view-specific data to achieve clustering alignment. However, existing multi-view …
Multi-level feature learning for contrastive multi-view clustering
Multi-view clustering can explore common semantics from multiple views and has attracted
increasing attention. However, existing works punish multiple objectives in the same feature …
increasing attention. However, existing works punish multiple objectives in the same feature …