A neural network model of associative memory is presented which unifies the two historically more relevant enhancements to the basic Little-Hopfield discrete model: the graded resp...
Enrique Carlos Segura Meccia, Roberto P. J. Perazz...
Consistency techniques are an e cient way of tackling constraint satisfaction problems (CSP). In particular, various arc-consistency algorithms have been designed such as the time...
Abstract—A general variational framework for image approximation and segmentation is introduced. By using a continuous “line-process” to represent edge boundaries, it is poss...
Despite the numerous optimization and evaluation studies that have been conducted with TLBs over the years, there is still a deficiency in an indepth understanding of TLB characte...
Traditional query processors generate full, accurate query results, either in batch or in pipelined fashion. We argue that this strict model is too rigid for exploratory queries o...