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-Task Learning (MTL) is a learning paradigm in machine learning and its aim is to
leverage useful information contained in multiple related tasks to help improve the …

With advances in information acquisition technologies, multi-view data become ubiquitous.
Multi-view learning has thus become more and more popular in machine learning and data …

Spectral clustering (SC) has become one of the most widely-adopted clustering algorithms,
and been successfully applied into various applications. We in this work explore the problem …

Multi-view clustering and multi-task clustering attract much attention in recent years. With the
development of data mining, a new learning scenario containing the properties of multi-task …

Multi-task clustering and multi-view clustering have severally found wide applications and
received much attention in recent years. Nevertheless, there are many clustering problems …

Multitask image clustering approaches intend to improve the model accuracy on each task
by exploring the relationships of multiple related image clustering tasks. However, most …

In the past decades, spectral clustering (SC) has become one of the most effective clustering
algorithms. However, most previous studies focus on spectral clustering tasks with a fixed …

Unsupervised learning has been widely used in many real-world applications. One of the
simplest and most important unsupervised learning models is the Gaussian mixture model …

Multi-task clustering and multi-view clustering have severally found wide applications and
received much attention in recent years. Nevertheless, there are many clustering problems …