This paper introduces a semi-supervised distance metric learning algorithm which uses pair-wise equivalence (similarity and dissimilarity) constraints to improve the original dist...
Abstract. We propose two differential geometric representations of planar shapes using: (i) direction functions and (ii) curvature functions, of their boundaries. Under either rep...
Anuj Srivastava, Washington Mio, Eric Klassen, Sha...
Unsupervised learning requires a grouping step that defines which data belong together. A natural way of grouping in images is the segmentation of objects or parts of objects. Whi...
Various problems in machine learning, databases, and statistics involve pairwise distances among a set of objects. It is often desirable for these distances to satisfy the propert...
In this paper we revise the penalty term of the Bayesian Information Criterion (BIC). Based on our previous approach to penalize each cluster only with its corresponding effective...