High level modeling and (quantitative) performance analysis of signal processing systems requires high level models for the applications(algorithms) and the implementations (archi...
Ed F. Deprettere, Edwin Rijpkema, Paul Lieverse, B...
Abstract. While there is strong motivation for using Gaussian Processes (GPs) due to their excellent performance in regression and classification problems, their computational com...
Learning Classifier Systems (LCSs), such as the accuracy-based XCS, evolve distributed problem solutions represented by a population of rules. During evolution, features are speci...
Martin V. Butz, Martin Pelikan, Xavier Llorà...
The MapReduce programming model simplifies large-scale data processing on commodity clusters by having users specify a map function that processes input key/value pairs to generate...
Joins are essential for many data analysis tasks, but are not supported directly by the MapReduce paradigm. While there has been progress on equi-joins, implementation of join alg...