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» A framework for the description of evolutionary algorithms
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FOCS
2009
IEEE
14 years 2 months ago
A Complete Characterization of Statistical Query Learning with Applications to Evolvability
Statistical query (SQ) learning model of Kearns is a natural restriction of the PAC learning model in which a learning algorithm is allowed to obtain estimates of statistical prop...
Vitaly Feldman
ICDAR
1999
IEEE
13 years 12 months ago
Methodology for Flexible and Efficient Analysis of the Performance of Page Segmentation Algorithms
This paper presents part of a new DIA performance analysis framework aimed at Layout Analysis algorithm developers. A new region-representation scheme (an interval-based descripti...
Apostolos Antonacopoulos, A. Brough
IJON
2006
99views more  IJON 2006»
13 years 7 months ago
Learning vector quantization: The dynamics of winner-takes-all algorithms
Winner-Takes-All (WTA) prescriptions for Learning Vector Quantization (LVQ) are studied in the framework of a model situation: Two competing prototype vectors are updated accordin...
Michael Biehl, Anarta Ghosh, Barbara Hammer
GECCO
2007
Springer
201views Optimization» more  GECCO 2007»
14 years 1 months ago
A parallel framework for loopy belief propagation
There are many innovative proposals introduced in the literature under the evolutionary computation field, from which estimation of distribution algorithms (EDAs) is one of them....
Alexander Mendiburu, Roberto Santana, Jose Antonio...
WEBI
2005
Springer
14 years 1 months ago
The WebCAT Framework - Automatic Generation of Meta-Data for Web Resources
Automated methods for resource annotation are a clear necessity, as the success of the Semantic Web depends on the availability of Web resources with meta-data conforming to known...
Bruno Martins, Mário J. Silva