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» Constraint Solving for Interpolation
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AI
1999
Springer
15 years 5 months ago
Bucket Elimination: A Unifying Framework for Reasoning
Bucket elimination is an algorithmic framework that generalizes dynamic programming to accommodate many problem-solving and reasoning tasks. Algorithms such as directional-resolut...
Rina Dechter
TIT
1998
78views more  TIT 1998»
15 years 5 months ago
Stationary Markov Random Fields on a Finite Rectangular Lattice
—This paper provides a complete characterization of stationary Markov random fields on a finite rectangular (nontoroidal) lattice in the basic case of a second-order neighborho...
Fréderic Champagnat, Jérôme Id...
TWC
2008
235views more  TWC 2008»
15 years 5 months ago
Optimal spectrum sensing framework for cognitive radio networks
Spectrum sensing is the key enabling technology for cognitive radio networks. The main objective of spectrum sensing is to provide more spectrum access opportunities to cognitive r...
Won-Yeol Lee, Ian F. Akyildiz
168
Voted
CORR
2010
Springer
105views Education» more  CORR 2010»
15 years 4 months ago
Optimism in Reinforcement Learning Based on Kullback-Leibler Divergence
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
Sarah Filippi, Olivier Cappé, Aurelien Gari...
LPAR
2010
Springer
15 years 4 months ago
On the Complexity of Model Expansion
Abstract. We study the complexity of model expansion (MX), which is the problem of expanding a given finite structure with additional relations to produce a finite model of a giv...
Antonina Kolokolova, Yongmei Liu, David G. Mitchel...