The development of information gathering and extraction technology has led to the
popularity of multi-view data, which enables samples to be seen from numerous …

Multi-view subspace clustering aims to discover the hidden subspace structures from
multiple views for robust clustering, and has been attracting considerable attention in recent …

Electrocardiogram (ECG) is a widely used technique to diagnose cardiovascular diseases. It
is a non-invasive technique that represents the cyclic contraction and relaxation of heart …

Abstract Recently, Multi-view Representation Learning (MRL) has drawn immense
attentions in the analysis of multi-source data and ubiquitously employed across different …

The existing clustering validity indexes (CVIs) show some difficulties to produce the correct
cluster number when some cluster centers are close to each other, and the separation …

Multi-view clustering (MVC), which effectively fuses information from multiple views for better
performance, has received increasing attention. Most existing MVC methods assume that …

Kernel method is a proven technique in multi-view learning. It implicitly defines a Hilbert
space where samples can be linearly separated. Most kernel-based multi-view learning …

Multi-view clustering is widely used to improve clustering performance. Recently, the
subspace clustering tensor learning method based on Markov chain is a crucial branch of …

Learning a comprehensive representation from multiview data is crucial in many real-world
applications. Multiview representation learning (MRL) based on nonnegative matrix …

Multiview subspace clustering (MVSC) has been used to explore the internal structure of
multiview datasets by revealing unique information from different views. Most existing …