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» Stochastic complexity in learning
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BC
2002
193views more  BC 2002»
15 years 6 months ago
Resonant spatiotemporal learning in large random recurrent networks
Taking a global analogy with the structure of perceptual biological systems, we present a system composed of two layers of real-valued sigmoidal neurons. The primary layer receives...
Emmanuel Daucé, Mathias Quoy, Bernard Doyon
172
Voted
ICGI
2010
Springer
15 years 5 months ago
Learning PDFA with Asynchronous Transitions
In this paper we extend the PAC learning algorithm due to Clark and Thollard for learning distributions generated by PDFA to automata whose transitions may take varying time length...
Borja Balle, Jorge Castro, Ricard Gavaldà
178
Voted
IJRR
2011
159views more  IJRR 2011»
15 years 1 months ago
Learning visual representations for perception-action systems
We discuss vision as a sensory modality for systems that effect actions in response to perceptions. While the internal representations informed by vision may be arbitrarily compl...
Justus H. Piater, Sébastien Jodogne, Renaud...
BMCBI
2011
15 years 1 months ago
Statistical learning techniques applied to epidemiology: a simulated case-control comparison study with logistic regression
Background: When investigating covariate interactions and group associations with standard regression analyses, the relationship between the response variable and exposure may be ...
John J. Heine, Walker H. Land Jr., Kathleen M. Ega...
CORR
2012
Springer
170views Education» more  CORR 2012»
14 years 2 months ago
What Cannot be Learned with Bethe Approximations
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
Uri Heinemann, Amir Globerson