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 …
Neighbor group structure preserving based consensus graph learning for incomplete multi-view clustering
In the area of clustering, multi-view clustering has drawn a lot of research attention by
making full use of information from different views. In many practical applications, collecting …
making full use of information from different views. In many practical applications, collecting …
Incomplete multi-view learning: Review, analysis, and prospects
Multi-view data, stemming from diverse information sources, often suffer from
incompleteness due to various factors such as equipment failure and data transmission …
incompleteness due to various factors such as equipment failure and data transmission …
Dynamic graph convolutional networks by semi-supervised contrastive learning
The traditional graph convolutional network (GCN) and its variants usually only propagate
node information through the topology given by the dataset. However, the given topology …
node information through the topology given by the dataset. However, the given topology …
Fractal belief Rényi divergence with its applications in pattern classification
Multisource information fusion is a comprehensive and interdisciplinary subject. Dempster-
Shafer (DS) evidence theory copes with uncertain information effectively. Pattern …
Shafer (DS) evidence theory copes with uncertain information effectively. Pattern …
Tensor-based consensus learning for incomplete multi-view clustering
As a challenging task in the field of unsupervised learning, incomplete multi-view clustering
can fully utilize multi-view information in the absence of partial views. Nevertheless, most …
can fully utilize multi-view information in the absence of partial views. Nevertheless, most …
Efficient multi-view graph clustering with local and global structure preservation
Anchor-based multi-view graph clustering (AMVGC) has received abundant attention owing
to its high efficiency and the capability to capture complementary structural information …
to its high efficiency and the capability to capture complementary structural information …
A Survey and an Empirical Evaluation of Multi-view Clustering Approaches
L Zhou, G Du, K Lü, L Wang, J Du - ACM Computing Surveys, 2024 - dl.acm.org
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 …
Multi-view MERA subspace clustering
Tensor-based multi-view subspace clustering (MSC) can capture high-order correlation in
the self-representation tensor. Current tensor decompositions for MSC suffer from highly …
the self-representation tensor. Current tensor decompositions for MSC suffer from highly …