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JMLR
2006
169views more  JMLR 2006»
13 years 9 months ago
Bayesian Network Learning with Parameter Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
AMAI
2004
Springer
14 years 2 months ago
Approximate Probabilistic Constraints and Risk-Sensitive Optimization Criteria in Markov Decision Processes
The majority of the work in the area of Markov decision processes has focused on expected values of rewards in the objective function and expected costs in the constraints. Althou...
Dmitri A. Dolgov, Edmund H. Durfee
ECCC
2006
145views more  ECCC 2006»
13 years 9 months ago
Constraint satisfaction: a personal perspective
Attempts at classifying computational problems as polynomial time solvable, NP-complete, or belonging to a higher level in the polynomial hierarchy, face the difficulty of undecid...
Tomás Feder
AAAI
2000
13 years 10 months ago
DATALOG with Constraints - An Answer-Set Programming System
Answer-set programming (ASP) has emerged recently as a viable programming paradigm well attuned to search problems in AI, constraint satisfaction and combinatorics. Propositional ...
Deborah East, Miroslaw Truszczynski
AMAI
1999
Springer
13 years 8 months ago
Logic Programs with Stable Model Semantics as a Constraint Programming Paradigm
Logic programming with the stable model semantics is put forward as a novel constraint programming paradigm. This paradigm is interesting because it bring advantages of logic prog...
Ilkka Niemelä