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JMLR
2006
169views more  JMLR 2006»
15 years 4 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 ...
FLAIRS
2006
15 years 5 months ago
Which Dynamic Constraint Problems Can Be Solved By Ants?
There exist a number of algorithms that can solve dynamic constraint satisfaction/optimization problems (DynCSPs or DynCOPs). Because of the large variety in the characteristics o...
Koenraad Mertens, Tom Holvoet, Yolande Berbers
GD
2006
Springer
15 years 8 months ago
Planarity Testing and Optimal Edge Insertion with Embedding Constraints
The planarization method has proven to be successful in graph drawing. The output, a combinatorial planar embedding of the so-called planarized graph, can be combined with state-o...
Carsten Gutwenger, Karsten Klein, Petra Mutzel
JAIR
2010
130views more  JAIR 2010»
15 years 2 months ago
A Constraint Satisfaction Framework for Executing Perceptions and Actions in Diagrammatic Reasoning
Diagrammatic reasoning (DR) is pervasive in human problem solving as a powerful adjunct to symbolic reasoning based on language-like representations. The research reported in this...
Bonny Banerjee, B. Chandrasekaran
CORR
2006
Springer
150views Education» more  CORR 2006»
15 years 4 months ago
The approximability of MAX CSP with fixed-value constraints
In the maximum constraint satisfaction problem (Max CSP), one is given a finite collection of (possibly weighted) constraints on overlapping sets of variables, and the goal is to ...
Vladimir G. Deineko, Peter Jonsson, Mikael Klasson...