While the literature contains several adaptive sampling techniques for statistical comparison of competing simulated system configurations and for embedded statistical computation...
For many types of machine learning algorithms, one can compute the statistically optimal" way to select training data. In this paper, we review how optimal data selection tec...
David A. Cohn, Zoubin Ghahramani, Michael I. Jorda...
In this work, we investigate the security of anonymous wireless sensor networks. To lay down the foundations of a formal framework, we propose a new model for analyzing and evalua...
Quantification of statistical significance is essential for the interpretation of protein structural similarity. To address this, a random model for protein structure comparison w...
One of the key points in Estimation of Distribution Algorithms (EDAs) is the learning of the probabilistic graphical model used to guide the search: the richer the model the more ...