Small-world networks are networks in which the graphical diameter of the network is as small as the diameter of random graphs but whose nodes are highly clustered when compared wit...
The Densest k-subgraph problem (i.e. find a size k subgraph with maximum number of edges), is one of the notorious problems in approximation algorithms. There is a significant g...
In this paper, the effect of the dimensionality of data sets on the exploitation of synergy among known nearest neighbor (NN) editing and condensing tools is analyzed using a synt...
In this paper a new learning scheme for SAT is proposed. The originality of our approach arises from its ability to achieve clause learning even if no conflict occurs. This clear...
In this paper we show that iterative rounding is a powerful and flexible tool in the design of approximation algorithms for multiobjective optimization problems. We illustrate tha...