In this paper we deal with codes identifying sets of vertices in random networks; that is, (1, ≤ ℓ)-identifying codes. These codes enable us to detect sets of faulty processor...
Alan M. Frieze, Ryan Martin, Julien Moncel, Mikl&o...
We study the problem of designing a survivable WDM network based on covering the communication requests with subnetworks that are protected independently from each other. We consi...
The Support Vector Machine (SVM) of Vapnik [9] has become widely established as one of the leading approaches to pattern recognition and machine learning. It expresses predictions...
We study a sparse coding learning algorithm that allows for a simultaneous learning of the data sparseness and the basis functions. The algorithm is derived based on a generative m...
A Quasi-Monte-Carlo method based on the computation of a surrogate model of the fitness function is proposed, and its convergence at super-linear rate 3/2 is proved under rather ...