In recent years, the advances in data collection and statistical analysis promotes canonical
correlation analysis (CCA) available for more advanced research. CCA is the main …

Anchor graph has been recently proposed to accelerate multi-view graph clustering and
widely applied in various large-scale applications. Different from capturing full instance …

Myoelectric interfaces have received much attention in the field of prosthesis control, neuro-
rehabilitation systems and human-computer interaction. However, when different users …

Without the valuable label information to guide the learning process, it is demanding to fully
excavate and integrate the underlying information from different views to learn the unified …

This book organizes principles and methods of signal processing and machine learning into
the framework of coherence. The book contains a wealth of classical and modern methods …

In this work, we devote ourselves to the challenging task of Unsupervised Multi-view
Representation Learning (UMRL), which requires learning a unified feature representation …

Many unsupervised multi-view representation learning (MRL) techniques have been
devised as multi-view data becomes more common in real-world applications. However …

Recent years have witnessed the increasing attentions on human action recognition (HAR).
Traditional methods are prone to explore the optimum spatiotemporal feature representation …

Canonical correlation analysis (CCA) matters in multiview representation learning. But, CCA
and its most variants are essentially based on explicit or implicit covariance matrices. It …

Feature is a crucial element of polarimetric synthetic aperture radar (PolSAR) image
classification. Multiple types of Features, such as polarimetric features (PF) generated from …