Recently, multi-view representation learning has become a rapidly growing direction in
machine learning and data mining areas. This paper introduces two categories for multi …

Abstract Multi-View Representation Learning (MVRL) aims to discover a shared
representation of observations from different views with the complex underlying correlation …

Multi-view learning is an emerging direction in machine learning which considers learning
with multiple views to improve the generalization performance. Multi-view learning is also …

In recent years, a great many methods of learning from multi-view data by considering the
diversity of different views have been proposed. These views may be obtained from multiple …

Despite multi-view learning progressed fast in past decades, it is still challenging due to the
difficulty in modeling complex correlation among different views, especially under the …

This paper focuses on the specific problem of multiview learning where samples have the
same feature set but different probability distributions, eg, different viewpoints or different …

Abstract Recently, Multi-view Representation Learning (MRL) has drawn immense
attentions in the analysis of multi-source data and ubiquitously employed across different …

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 learning or learning with multiple distinct feature sets is a rapidly growing
direction in machine learning with well theoretical underpinnings and great practical …

Multiview learning has received extensive research interest and has demonstrated
promising results in recent years. Despite the progress made, there are two significant …