Over the last decade, it has been demonstrated that many systems in science and
engineering can be modeled more accurately by fractional-order than integer-order …

Canonical correlation analysis is a family of multivariate statistical methods for the analysis
of paired sets of variables. Since its proposition, canonical correlation analysis has, for …

Fractional calculus is an abstract idea exploring interpretations of differentiation having non-
integer order. For a very long time, it was considered as a topic of mere theoretical interest …

Multi-view data represented by different features have been involved in many machine
learning applications. Efficiently exploiting and preserving the correlative yet complementary …

Recently, a multi-view dictionary learning (DL) technique has received much attention.
Although some multi-view DL methods have been presented, they suffer from the problem of …

To address the challenging task of diagnosing neurodegenerative brain disease, such as
Alzheimer's disease (AD) and mild cognitive impairment (MCI), we propose a novel method …

Multi-label canonical correlation analysis (ml-CCA) has been developed for cross-modal
retrieval. However, the computation of ml-CCA involves dense matrices …

In order to process multi-view multi-label data sets, we propose global and local multi-view
multi-label learning (GLMVML). This method can exploit global and local label correlations …

Feature embedding aims to learn a low-dimensional vector representation for each instance
to preserve the information in its features. These representations can benefit various offthe …

Set-based video recognition is an important application in practice, and many specialized
approaches have been proposed. However, most of these methods either only use one kind …