Online learning represents a family of machine learning methods, where a learner attempts
to tackle some predictive (or any type of decision-making) task by learning from a sequence …

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 …

Multiview learning (MVL), which enhances the learners' performance by coordinating
complementarity and consistency among different views, has attracted much attention. The …

Support vector machine (SVM) is an optimal margin based classification technique in
machine learning. SVM is a binary linear classifier which has been extended to non-linear …

This survey aims at providing a state-of-the-art overview of feature selection and fusion
strategies, which select and combine multi-view features effectively to accomplish …

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 …

This paper presents a general multi-view feature extraction approach that we call
Generalized Multiview Analysis or GMA. GMA has all the desirable properties required for …

In the field of intelligent transportation, transfer learning (TL) is often used to recognize EEG-
based drowsy driving for a new subject with few subject-specific calibration data. However …

Canonical correlation analysis (CCA) has proven an effective tool for two-view dimension
reduction due to its profound theoretical foundation and success in practical applications. In …

The k-means clustering algorithm is the oldest and most known method in cluster analysis. It
has been widely studied with various extensions and applied in a variety of substantive …