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» Learning and Inference with Constraints
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CP
2007
Springer
16 years 21 days ago
GAC Via Unit Propagation
In this paper we argue that an attractive and potentially very general way of achieving generalized arc consistency (GAC) on a constraint is by using unit propagation (UP) over a C...
Fahiem Bacchus
CIG
2005
IEEE
16 years 4 days ago
Nannon: A Nano Backgammon for Machine Learning Research
A newly designed game is introduced, which feels like Backgammon, but has a simplified rule set. Unlike earlier attempts at simplifying the game, Nannon maintains enough features a...
Jordan B. Pollack
ICML
2000
IEEE
15 years 11 months ago
A Bayesian Framework for Reinforcement Learning
The reinforcement learning problem can be decomposed into two parallel types of inference: (i) estimating the parameters of a model for the underlying process; (ii) determining be...
Malcolm J. A. Strens
ICANN
2010
Springer
15 years 4 months ago
Learning in a Unitary Coherent Hippocampus
Abstract. A previous paper [2] presented a model (UCPF-HC) of the hippocampus as a unitary coherent particle filter, which combines the classical hippocampal roles of associative m...
Charles W. Fox, Tony J. Prescott
ICML
2009
IEEE
16 years 7 months ago
Herding dynamical weights to learn
A new "herding" algorithm is proposed which directly converts observed moments into a sequence of pseudo-samples. The pseudosamples respect the moment constraints and ma...
Max Welling