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» Strongly Non-U-Shaped Learning Results by General Techniques
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COLT
2010
Springer
11 years 9 months ago
Strongly Non-U-Shaped Learning Results by General Techniques
In learning, a semantic or behavioral U-shape occurs when a learner rst learns, then unlearns, and, nally, relearns, some target concept (on the way to success). Within the framew...
John Case, Timo Kötzing
COLT
1997
Springer
12 years 4 months ago
General Convergence Results for Linear Discriminant Updates
The problem of learning linear discriminant concepts can be solved by various mistake-driven update procedures, including the Winnow family of algorithms and the well-known Percep...
Adam J. Grove, Nick Littlestone, Dale Schuurmans
ICML
2005
IEEE
13 years 17 days ago
A general regression technique for learning transductions
The problem of learning a transduction, that is a string-to-string mapping, is a common problem arising in natural language processing and computational biology. Previous methods ...
Corinna Cortes, Mehryar Mohri, Jason Weston
GEOINFORMATICA
1998
96views more  GEOINFORMATICA 1998»
11 years 11 months ago
Experiments with Learning Techniques for Spatial Model Enrichment and Line Generalization
The nature of map generalization may be non-uniform along the length of an individual line, requiring the application of methods that adapt to the local geometry and the geographi...
Corinne Plazanet, Nara Martini Bigolin, Anne Ruas
ICCV
2009
IEEE
11 years 9 months ago
Kernel map compression using generalized radial basis functions
The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machin...
Omar Arif, Patricio A. Vela
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