This paper describes a novel approach to nd a tighter bound of the transformation of the Min-Max problems into the one of Least-Square Estimation. It is well known that the above ...
Evolutionary and genetic algorithms (EAs and GAs) are quite successful randomized function optimizers. This success is mainly based on the interaction of different operators like ...
In this paper we propose a new algorithm for learning polyhedral classifiers. In contrast to existing methods for learning polyhedral classifier which solve a constrained optimiza...
Data is typically replicated in a Data Grid to improve the job response time and data availability. Strategies for data replication in a Data Grid have previously been proposed, b...
In this paper, we design a novel MRF framework which is called Non-Local Range Markov Random Field (NLRMRF). The local spatial range of clique in traditional MRF is extended to th...