We consider the problem of fitting metric data on n points to a path (line) metric. Our objective is to minimize the total additive distortion of this mapping. The total additive ...
We present randomized approximation algorithms for the circular arc graph colouring problem and for the problem of bandwidth allocation in all-optical ring networks. We obtain a fa...
Clustering is of central importance in a number of disciplines including Machine Learning, Statistics, and Data Mining. This paper has two foci: 1 It describes how existing algori...
A linear time approximate maximum likelihood decoding algorithm on tail-biting trellises is presented, that requires exactly two rounds on the trellis. This is an adaptation of an ...
A new framework is presented that uses tools from duality theory of linear programming to derive graph-cut based combinatorial algorithms for approximating NP-hard classification ...