We explore a new Bayesian model for probabilistic grammars, a family of distributions over discrete structures that includes hidden Markov models and probabilistic context-free gr...
This paper proposes an original model of the execution time of assembly instructions in superscalar architectures. The approach is based on a rigorous mathematical model and provi...
William Fornaciari, Vito Trianni, Carlo Brandolese...
Background: A growing demand for tools to assist the building and analysis of biological networks exists in systems biology. We argue that the use of a formal approach is relevant...
constraint abstractions into integer programming, and to discuss possible combinations of the two approaches. Combinatorial problems are ubiquitous in many real world applications ...
We study the problem of learning to rank images for image retrieval. For a noisy set of images indexed or tagged by the same keyword, we learn a ranking model from some training e...