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» Approximate algorithms for neural-Bayesian approaches
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EC
2006
121views ECommerce» more  EC 2006»
14 years 9 months ago
A Study of Structural and Parametric Learning in XCS
The performance of a learning classifier system is due to its two main components. First, it evolves new structures by generating new rules in a genetic process; second, it adjust...
Tim Kovacs, Manfred Kerber
JMLR
2008
150views more  JMLR 2008»
14 years 9 months ago
Discriminative Learning of Max-Sum Classifiers
The max-sum classifier predicts n-tuple of labels from n-tuple of observable variables by maximizing a sum of quality functions defined over neighbouring pairs of labels and obser...
Vojtech Franc, Bogdan Savchynskyy
92
Voted
JSAC
2006
107views more  JSAC 2006»
14 years 9 months ago
Adaptive Sensor Activity Control in Many-to-One Sensor Networks
Abstract--In this paper, we consider a many-to-one sensor network where a large number of sensors are deployed to monitor a physical environment. We explore sensor activity managem...
Zhifeng Hu, Junshan Zhang, Lang Tong
TCBB
2010
106views more  TCBB 2010»
14 years 4 months ago
Quantifying the Degree of Self-Nestedness of Trees: Application to the Structural Analysis of Plants
In this paper we are interested in the problem of approximating trees by trees with a particular self-nested structure. Self-nested trees are such that all their subtrees of a give...
Christophe Godin, Pascal Ferraro
SIGMOD
2011
ACM
269views Database» more  SIGMOD 2011»
14 years 14 days ago
Advancing data clustering via projective clustering ensembles
Projective Clustering Ensembles (PCE) are a very recent advance in data clustering research which combines the two powerful tools of clustering ensembles and projective clustering...
Francesco Gullo, Carlotta Domeniconi, Andrea Tagar...