Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
This paper presents a novel partial assignment technique (PAT) that decides which tasks should be assigned to the same resource without explicitly defining assignment of these tas...
Optimization problems are more and more complex and their resource requirements are ever increasing. Although metaheuristics allow to significantly reduce the computational complex...
Process network problems can be formulated as Generalized Disjunctive Programs where a logicbased representation is used to deal with the discrete and continuous decisions. A new ...
In this paper, a novel approximate link-state dissemination framework, called TROP, is proposed for shared backup path protection (SBPP) in Multi-Protocol Label Switching (MPLS) ne...