Deep clustering: A comprehensive survey
Cluster analysis plays an indispensable role in machine learning and data mining. Learning
a good data representation is crucial for clustering algorithms. Recently, deep clustering …
a good data representation is crucial for clustering algorithms. Recently, deep clustering …
Self-supervised multimodal learning: A survey
Multimodal learning, which aims to understand and analyze information from multiple
modalities, has achieved substantial progress in the supervised regime in recent years …
modalities, has achieved substantial progress in the supervised regime in recent years …
Enhanced tensor low-rank and sparse representation recovery for incomplete multi-view clustering
Incomplete multi-view clustering (IMVC) has attracted remarkable attention due to the
emergence of multi-view data with missing views in real applications. Recent methods …
emergence of multi-view data with missing views in real applications. Recent methods …
Adaptive feature projection with distribution alignment for deep incomplete multi-view clustering
Incomplete multi-view clustering (IMVC) analysis, where some views of multi-view data
usually have missing data, has attracted increasing attention. However, existing IMVC …
usually have missing data, has attracted increasing attention. However, existing IMVC …
Gcfagg: Global and cross-view feature aggregation for multi-view clustering
Multi-view clustering can partition data samples into their categories by learning a
consensus representation in unsupervised way and has received more and more attention …
consensus representation in unsupervised way and has received more and more attention …
UNTIE: Clustering analysis with disentanglement in multi-view information fusion
Multi-view clustering focuses on exploring cluster structures among multiple views and is an
effective approach to achieve multi-view information fusion without requiring label …
effective approach to achieve multi-view information fusion without requiring label …
Multiplex graph representation learning via dual correlation reduction
Recently, with the superior capacity for analyzing the multiplex graph data, self-supervised
multiplex graph representation learning (SMGRL) has received much interest. However …
multiplex graph representation learning (SMGRL) has received much interest. However …
Dealmvc: Dual contrastive calibration for multi-view clustering
Benefiting from the strong view-consistent information mining capacity, multi-view
contrastive clustering has attracted plenty of attention in recent years. However, we observe …
contrastive clustering has attracted plenty of attention in recent years. However, we observe …
Dicnet: Deep instance-level contrastive network for double incomplete multi-view multi-label classification
In recent years, multi-view multi-label learning has aroused extensive research enthusiasm.
However, multi-view multi-label data in the real world is commonly incomplete due to the …
However, multi-view multi-label data in the real world is commonly incomplete due to the …
Cross-view topology based consistent and complementary information for deep multi-view clustering
Multi-view clustering aims to extract valuable information from different sources or
perspectives. Over the years, the deep neural network has demonstrated its superior …
perspectives. Over the years, the deep neural network has demonstrated its superior …