In this paper, a new deep incomplete multi-view clustering network, called DIMC-net, is
proposed to address the challenge of multi-view clustering on missing views. In particular …

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 …

Deep convolutional neural networks (CNNs) for image denoising have recently attracted
increasing research interest. However, plain networks cannot recover fine details for a …

In this paper, we propose a general framework for incomplete multiview clustering. The
proposed method is the first work that exploits the graph learning and spectral clustering …

Palmprint recognition has been widely used in security authentication. However, most of the
existing palmprint representation methods are focused on a special application scenario …

Since human-labeled samples are free for the target set, unsupervised person re-
identification (Re-ID) has attracted much attention in recent years, by additionally exploiting …

With the widespread development of the internet, multi-view text documents have become
increasingly common, which has led to extensive research on multi-view text document …

This work investigates the medical image denoising (MID) application of the dual denoising
network (DudeNet) model for chest X-ray (CXR). The DudeNet model comprises four …

Multi-view support vector machines (MvSVMs) have been widely used to solve multi-view
classification problems. However, the conventional MvSVMs often overlook the presence of …

An increasing number of related urban data sources have brought forth novel opportunities
for learning urban region representations, ie, embeddings. The embeddings describe latent …