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ICML
2009
IEEE
14 years 8 months ago
Structure learning of Bayesian networks using constraints
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 ...
Cassio Polpo de Campos, Zhi Zeng, Qiang Ji
CORR
2006
Springer
113views Education» more  CORR 2006»
13 years 7 months ago
Combining typing and size constraints for checking the termination of higher-order conditional rewrite systems
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 ...
Frédéric Blanqui, Colin Riba
AIPS
2004
13 years 9 months ago
Heuristic Refinements of Approximate Linear Programming for Factored Continuous-State Markov Decision Processes
Approximate linear programming (ALP) offers a promising framework for solving large factored Markov decision processes (MDPs) with both discrete and continuous states. Successful ...
Branislav Kveton, Milos Hauskrecht
CSL
2004
Springer
14 years 1 months ago
Set Constraints on Regular Terms
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...
Pawel Rychlikowski, Tomasz Truderung
ER
2009
Springer
92views Database» more  ER 2009»
14 years 2 months ago
On Matrix Representations of Participation Constraints
Abstract. We discuss the existence of matrix representations for generalised and minimum participation constraints which are frequently used in database design and conceptual model...
Sven Hartmann, Uwe Leck, Sebastian Link