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» Learning and Inference with Constraints
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CP
2007
Springer
16 years 1 months 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
196
Voted
CIG
2005
IEEE
16 years 20 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
198
Voted
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 5 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
204
Voted
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