This paper describes research in methods to discover Web Service Description Language (WSDL) documents. This work extends current discovery research through use of the Google Web ...
We consider the problem of embedding a metric into low-dimensional Euclidean space. The classical theorems of Bourgain, and of Johnson and Lindenstrauss say that any metric on n p...
Metric and kernel learning arise in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional d...
Prateek Jain, Brian Kulis, Jason V. Davis, Inderji...
Background: The search for cluster structure in microarray datasets is a base problem for the so-called “-omic sciences”. A difficult problem in clustering is how to handle da...
This paper addresses the problem of calibrating a pinhole camera from images of an isoceles trapezoid. Assuming a unit aspect ratio and zero skew, we introduce a novel and simple ...