The need for appropriate ways to measure the distance or similarity between data is
ubiquitous in machine learning, pattern recognition and data mining, but handcrafting such …

The expansion of the Internet over the last decade and the proliferation of online social
communities, such as Facebook, Google+, and Twitter, as well as multimedia sharing sites …

The impact-echo (IE) acoustic inspection method is a non-destructive evaluation technique,
which has been widely applied to detect the defects, structural deterioration level, and …

Metric learning has become a very active research field. The most popular representative--
Mahalanobis metric learning--can be seen as learning a linear transformation and then …

Metric learning makes it plausible to learn semantically meaningful distances for complex
distributions of data using label or pairwise constraint information. However, to date, most …

Distance metric learning aims to learn from the given training data a valid distance metric,
with which the similarity between data samples can be more effectively evaluated for …

This book provides a comprehensive introduction to the use of graph analysis in the study of
social media and digital media. It covers the following topics: graphs in social media, graph …

Rolling bearings are one of the most vulnerable parts in rotating machines. This paper
presents a novel approach to identify the rolling bearings fault based on variational mode …

Dictionary learning approaches have been widely applied to solve pattern classification
problems and have achieved promising performance. However, most of works aim to learn a …

The key to success of many machine learning and pattern recognition algorithms is the way
of computing distances between the input data. In this paper, we propose a large-margin …