We consider the problem of learning a similarity function from a set of positive equivalence constraints, i.e. 'similar' point pairs. We define the similarity in informa...
Currently, a huge amount of biological data can be naturally represented by graphs, e.g., protein interaction networks, gene regulatory networks, etc. The need for indexing large ...
Object detection in clutter or occlusion is a hard problem in computer vision. We propose an object detection method based on contour grouping. Two stages are included: a novel di...
There are many emerging database applications that require accurate selectivity estimation of approximate string matching queries. Edit distance is one of the most commonly used s...
This paper addresses the problem of efficient information theoretic, non-parametric data clustering. We develop a procedure for adapting the cluster memberships of the data pattern...
Robert Jenssen, Deniz Erdogmus, Kenneth E. Hild II...