Abstract. Parallelizing a sequential algorithm—i.e., manually or automatically converting it into an equivalent parallel distributed algorithm—is an important problem. Ideally,...
Lei Pan, Ming Kin Lai, Michael B. Dillencourt, Lub...
This paper presents the design and analysis of parallel approximation algorithms for facility-location problems, including NC and RNC algorithms for (metric) facility location, k-...
In this paper we analyze the PAC learning abilities of several simple iterative algorithms for learning linear threshold functions, obtaining both positive and negative results. W...
The generic Multi-objective Evolutionary Algorithm (MOEA) aims to produce Pareto-front approximations with good convergence and diversity property. To achieve convergence, most mu...
For the past few years researches have been investigating enhancing tracking performance by combining several different tracking algorithms. We propose an analytically justified, ...