It is doubtless that intuitionistic fuzzy set (IFS) theory plays an increasingly important role in solving the problems under uncertain situation. As one of the most critical members in the theory, distance measure is widely used in many aspects. Nevertheless, it is a pity that part of the existing distance measures has some drawbacks in practical significance and accuracy. To make up for their...

Distance measures are used extensively in data mining and other types of data analysis. Such measures assume it is possible to compute for each pair of domain objects their mutual distance. Much of the research in distance measures concentrates on objects either in attribute-value representation or in first-order representation. With the increasing use of XML technology as a means for unambiguo...

This paper presents a distance-based discriminative framework for learning with probability distributions. Instead of using kernel mean embeddings or generalized radial basis kernels, we introduce embeddings based on dissimilarity of distributions to some reference distributions denoted as templates. Our framework extends the theory of similarity of Balcan et al. (2008) to the population distri...