Big multimedia data is heterogeneous in essence, that is, the data may be a mixture of
video, audio, text, and images. This is due to the prevalence of novel applications in recent …

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 …

k nearest neighbor (kNN) method is a popular classification method in data mining and
statistics because of its simple implementation and significant classification performance …

The K Nearest Neighbor (kNN) method has widely been used in the applications of data
mining and machine learning due to its simple implementation and distinguished …

K nearest neighbors (kNN) is an efficient lazy learning algorithm and has successfully been
developed in real applications. It is natural to scale the kNN method to the large scale …

In this paper, we review recent progresses in the area of mining data from multiple data
sources. The advancement of information communication technology has generated a large …

Common spatial pattern (CSP)-based spatial filtering has been most popularly applied to
electroencephalogram (EEG) feature extraction for motor imagery (MI) classification in brain …

Industrial automation effectively reduces the human effort in various activities of the industry.
In many autonomous systems, object recognition plays a vital role. Thus, finding a solution …

How do we retrieve images accurately? Also, how do we rank a group of images precisely
and efficiently for specific queries? These problems are critical for researchers and …

Previous multi-view spectral clustering methods are a two-step strategy, which first learns a
fixed common representation (or common affinity matrix) of all the views from original data …