Clustering is a machine learning paradigm of dividing sample subjects into a number of
groups such that subjects in the same groups are more similar to those in other groups. With …

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 …

While semi-supervised learning (SSL) has received tremendous attentions in many machine
learning tasks due to its successful use of unlabeled data, existing SSL algorithms use either …

Semi-supervised learning is the branch of machine learning concerned with using labelled
as well as unlabelled data to perform certain learning tasks. Conceptually situated between …

Deep learning has led to tremendous progress in the field of medical artificial intelligence.
However, training deep-learning models usually require large amounts of annotated data …

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 …

Extreme learning machines (ELMs) have proven to be efficient and effective learning
mechanisms for pattern classification and regression. However, ELMs are primarily applied …

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 …

Semi-supervised learning is a learning paradigm concerned with the study of how
computers and natural systems such as humans learn in the presence of both labeled and …

Deep neural networks, trained with large amount of labeled data, can fail to generalize well
when tested with examples from a target domain whose distribution differs from the training …