Recent research into single–objective continuous Estimation– of–Distribution Algorithms (EDAs) has shown that when maximum–likelihood estimations are used for parametric d...
Modern microprocessors can achieve high performance on linear algebra kernels but this currently requires extensive machine-speci c hand tuning. We have developed a methodology wh...
Jeff Bilmes, Krste Asanovic, Chee-Whye Chin, James...
The interesting properties of P2P systems (high availability despite peer volatility, support for heterogeneous architectures, high scalability, etc.) make them attractive for dist...
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...
This paper introduces a novel statistical mixture model for probabilistic grouping of distributional histogram data. Adopting the Bayesian framework, we propose to perform anneale...