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NECO
2010
97views more  NECO 2010»
13 years 6 months ago
Rademacher Chaos Complexities for Learning the Kernel Problem
In this paper we develop a novel generalization bound for learning the kernel problem. First, we show that the generalization analysis of the kernel learning problem reduces to in...
Yiming Ying, Colin Campbell
NECO
2010
129views more  NECO 2010»
13 years 6 months ago
A Two-Layer Model of Natural Stimuli Estimated with Score Matching
We consider a hierarchical two-layer model of natural signals in which both layers are learned from the data. Estimation is accomplished by Score Matching, a recently proposed est...
Urs Köster, Aapo Hyvärinen
NECO
2010
78views more  NECO 2010»
13 years 6 months ago
Hebbian Plasticity and Homeostasis in a Model of Hypercolumn of the Visual Cortex
Neurons in the nervous system display a wide variety of plasticity processes. Among them are covariance based rules and homeostatic plasticity. By themselves, the first ones tend...
R. Rossi Pool, G. Mato
NECO
2007
87views more  NECO 2007»
13 years 7 months ago
Reinforcement Learning State Estimator
cal networks in the learning of abstract and effector-specific representations of motor sequences. Neuroimage. 32, 714-727. (Neuroimage Editor’s Choice Award, 2006) Daw, N. D. Do...
Jun Morimoto, Kenji Doya
NECO
2000
95views more  NECO 2000»
13 years 7 months ago
Tilt Aftereffects in a Self-Organizing Model of the Primary Visual Cortex
RF-LISSOM, a self-organizing model of laterally connected orientation maps in the primary visual cortex, was used to study the psychological phenomenon known as the tilt aftereffe...
James A. Bednar, Risto Miikkulainen