Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Current literature offers a number of different approaches to what could generally be called “probabilistic logic programming”. These are usually based on Horn clauses. Here, ...
Joost Vennekens, Sofie Verbaeten, Maurice Bruynoog...
Abstract. We describe a cryptographically sound formal logic for proving protocol security properties without explicitly reasoning about probability, asymptotic complexity, or the ...
Anupam Datta, Ante Derek, John C. Mitchell, Vitaly...
I present MOSES (meta-optimizing semantic evolutionary search), a new probabilistic modeling (estimation of distribution) approach to program evolution. Distributions are not esti...
This paper improves a recently-presented approach to Web Personalization, named Community Web Directories, which applies personalization techniques to Web Directories. The Web dire...