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ICPR
2008
IEEE
14 years 2 months ago
Improving Bayesian Network parameter learning using constraints
This paper describes a new approach to unify constraints on parameters with training data to perform parameter estimation in Bayesian networks of known structure. The method is ge...
Cassio Polpo de Campos, Qiang Ji
TON
2012
11 years 10 months ago
Opportunistic Spectrum Access in Multiple-Primary-User Environments Under the Packet Collision Constraint
—Cognitive Radio (CR) technology has great potential to alleviate spectrum scarcity in wireless communications. It allows secondary users (SUs) to opportunistically access spectr...
Eric Jung, Xin Liu
SPAA
1990
ACM
13 years 11 months ago
Optimal Cooperative Search in Fractional Cascaded Data Structures
Fractional cascading is a technique designed to allow e cient sequential search in a graph with catalogs of total size n. The search consists of locating a key in the catalogs alo...
Roberto Tamassia, Jeffrey Scott Vitter
FLAIRS
2008
13 years 10 months ago
Conditional and Composite Constraints with Preferences
Preferences in constraint problems are common but significant in many real world applications. In this paper, we extend our conditional and composite CSP (CCCSP) framework, managi...
Malek Mouhoub, Amrudee Sukpan
EMO
2009
Springer
174views Optimization» more  EMO 2009»
14 years 2 months ago
Constraint Programming
To model combinatorial decision problems involving uncertainty and probability, we introduce stochastic constraint programming. Stochastic constraint programs contain both decision...
Pascal Van Hentenryck