Abstract. Writing e cient iterative solvers for irregular, sparse matrices in HPF is hard. The locality in the computations is unclear, and for e ciency we use storage schemes that...
Abstract. In this paper we present a novel approach to solving Constraint Satisfaction Problems whose constraint graphs are highly clustered and the graph of clusters is close to b...
Recurrent neural networks are able to store information about previous as well as current inputs. This "memory" allows them to solve temporal problems such as language r...
We propose a new framework based on Genetic Programming (GP) to automatically decompose problems into smaller and simpler tasks. The framework uses GP at two levels. At the top lev...
Using a recently proposed model for combinatorial landscapes, Local Optima Networks (LON), we conduct a thorough analysis of two types of instances of the Quadratic Assignment Prob...