This paper addresses exact learning of Bayesian network structure from data and expert's knowledge based on score functions that are decomposable. First, it describes useful ...
In a previous work, the first author extended to higher-order rewriting and dependent types the use of size annotations in types, a termination proof technique called type or size ...
Approximate linear programming (ALP) offers a promising framework for solving large factored Markov decision processes (MDPs) with both discrete and continuous states. Successful ...
Set constraints are a useful formalism for verifying properties of programs. Usually, they are interpreted over the universe of finite terms. However, some logic languages allow i...
Abstract. We discuss the existence of matrix representations for generalised and minimum participation constraints which are frequently used in database design and conceptual model...