The Earth Mover's distance was first introduced as a purely empirical way to measure texture and color similarities. We show that it has a rigorous probabilistic interpretati...
Abstract. We address the problem of entropy estimation for highdimensional finite-accuracy data. Our main application is evaluating high-order mutual information image similarity c...
Metric learning algorithms can provide useful distance functions for a variety of domains, and recent work has shown good accuracy for problems where the learner can access all di...
Prateek Jain, Brian Kulis, Inderjit S. Dhillon, Kr...
We present a novel approach to learn distance metric for information retrieval. Learning distance metric from a number of queries with side information, i.e., relevance judgements...
This paper considers a distance metric learning (DML) algorithm for a fingerprinting system, which identifies a query content by finding the fingerprint in the database (DB) that m...