Recent high throughput experimental methods have been used to collect large biomedical
omics datasets. Clustering of single omic datasets has proven invaluable for biological and …

High-throughput technologies have been used to generate a large amount of omics data. In
the past, single-level analysis has been extensively conducted where the omics …

Multi-view graph-based clustering aims to provide clustering solutions to multi-view data.
However, most existing methods do not give sufficient consideration to weights of different …

Networks are ubiquitous in biology where they encode connectivity patterns at all scales of
organization, from molecular to the biome. However, biological networks are noisy due to …

Convolutional neural network (CNN) has demonstrated impressive ability to represent
hyperspectral images and to achieve promising results in hyperspectral image classification …

Multiview data clustering attracts more attention than their single-view counterparts due to
the fact that leveraging multiple independent and complementary information from multiview …

Recent technologies have made it cost-effective to collect diverse types of genome-wide
data. Computational methods are needed to combine these data to create a comprehensive …

With the development of web technology, multi-modal or multi-view data has surged as a
major stream for big data, where each modal/view encodes individual property of data …

The proliferation of social media in communication and information dissemination has made
it an ideal platform for spreading rumors. Automatically debunking rumors at their stage of …

Multi-view clustering is a long-standing important task, however, it remains challenging to
exploit valuable information from the complex multi-view data located in diverse high …