This paper presents an efficient algorithm for learning Bayesian belief networks from databases. The algorithm takes a database as input and constructs the belief network structur...
In the present paper, we present the theoretical basis, as well as an empirical validation, of a protocol designed to obtain effective VC dimension estimations in the case of a si...
— This work presents a mathematical framework for the development of efficient algorithms for cyclic convolution computations. The framework is based on the Chinese Reminder Theo...
We present a model for representing search in theorem proving. This model captures the notion of contraction, which has been central in some of the recent developments in theorem ...
In the feature selection of cancer classification problems, many existing methods consider genes individually by choosing the top genes which have the most significant signal-to...