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 …

Incomplete multi-view clustering (IMVC) analysis, where some views of multi-view data
usually have missing data, has attracted increasing attention. However, existing IMVC …

The clinical diagnosis decision-making process of integrated traditional Chinese medicine
and Western medicine is essentially a type of group decision-making (GDM) problem, which …

Abstract Multi-View Clustering (MVC) is an emerging research area aiming to cluster
multiple views of the same data, which has recently drawn substantial attention. Various …

In real applications, it is often that the collected multiview data contain missing views. Most
existing incomplete multiview clustering (IMVC) methods cannot fully utilize the underlying …

Multiview pedestrian detection detects pedestrians based on the perception of the same
environment from multiple perspectives. This task requires feature extraction in a single view …

Multi-view clustering (MVC) focuses on adaptively partitioning data from diverse sources into
the respective groups and has been widely studied under the assumption of complete data …

Mutation point extraction in acoustic emission (AE) signals is always a complex and
challenging task since the mutation is often hidden in AE signals and with a short duration …

Incomplete multi-view clustering is pivotal in machine learning because complex systems
are inherently difficult to be fully observed and therefore pose a great challenge to revealing …

In the past decade, multi-view clustering has become a research hot spot of machine
learning. In traditional multi-view clustering methods, all views of the data points are …