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IEICET
2007
68views more  IEICET 2007»
13 years 9 months ago
Generalization Error Estimation for Non-linear Learning Methods
Estimating the generalization error is one of the key ingredients of supervised learning since a good generalization error estimator can be used for model selection. An unbiased g...
Masashi Sugiyama
IJON
2007
131views more  IJON 2007»
13 years 9 months ago
Margin-based active learning for LVQ networks
In this article, we extend a local prototype-based learning model by active learning, which gives the learner the capability to select training samples and thereby increase speed a...
Frank-Michael Schleif, Barbara Hammer, Thomas Vill...
ALT
2008
Springer
14 years 6 months ago
Numberings Optimal for Learning
This paper extends previous studies on learnability in non-acceptable numberings by considering the question: for which criteria which numberings are optimal, that is, for which nu...
Sanjay Jain, Frank Stephan
ICML
2010
IEEE
13 years 10 months ago
Nonparametric Return Distribution Approximation for Reinforcement Learning
Standard Reinforcement Learning (RL) aims to optimize decision-making rules in terms of the expected return. However, especially for risk-management purposes, other criteria such ...
Tetsuro Morimura, Masashi Sugiyama, Hisashi Kashim...
ICANN
2010
Springer
13 years 7 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