Attack resistance has been a critical concern for security-related applications. Various side-channel attacks can be launched to retrieve security information such as encryption k...
This paper presents a new approach to inference in Bayesian networks. The principal idea is to encode the network by logical sentences and to compile the resulting encoding into an...
Abstract. We develop a probabilistic interpretation of non-linear component extraction in neural networks that activate their hidden units according to a softmaxlike mechanism. On ...
The objective of this paper is to describe the use of a probabilistic approach to Web effort estimation by means of a Bayesian Network. A Bayesian Network is a model that embodies ...
This paper extends the use of stochastic watershed, recently introduced by Angulo and Jeulin [1], to unsupervised segmentation of multispectral images. Several probability density ...