A low-distortion embedding between two metric spaces is a mapping which preserves the distances between each pair of points, up to a small factor called distortion. Low-distortion...
Mihai Badoiu, Julia Chuzhoy, Piotr Indyk, Anastasi...
The hurdles in solving Constrained Optimization Problems (COP) arise from the challenge of searching a huge variable space in order to locate feasible points with acceptable solut...
Abu S. S. M. Barkat Ullah, Ruhul A. Sarker, David ...
This paper presents a new approach designed to reduce the computational load of the existing clustering algorithms by trimming down the documents size using fingerprinting methods...
In this paper we study how to improve nearest neighbor classification by learning a Mahalanobis distance metric. We build on a recently proposed framework for distance metric lear...
Proceedings of the 1998 IEEE International Conference on Computer Vision, Bombay, India We introduce a new distance between two distributions that we call the Earth Mover's D...