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 …

The global health landscape has been persistently challenged by the emergence and re-
emergence of infectious diseases. Traditional epidemiological models, rooted in the early …

In this article, we propose a unified framework to solve the following two challenging
problems in incomplete multi-view representation learning: i) how to learn a consistent …

Multi-view subspace clustering has attracted intensive attention to effectively fuse multi-view
information by exploring appropriate graph structures. Although existing works have made …

Despite the impressive clustering performance and efficiency in characterizing both the
relationship between the data and cluster structure, most existing graph-based multi-view …

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 …

Multi-view spectral clustering, which exploits the complementary information among graphs
of diverse views to obtain superior clustering results, has attracted intensive attention …

Multi-view subspace clustering has received widespread attention to effectively fuse multi-
view information among multimedia applications. Considering that most existing …

Multi-view clustering, which exploits the multi-view information to partition data into their
clusters, has attracted intense attention. However, most existing methods directly learn a …

Despite significant progress, there remain three limitations to the previous multi-view
clustering algorithms. First, they often suffer from high computational complexity, restricting …