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NIPS
1997
15 years 8 months ago
Learning Generative Models with the Up-Propagation Algorithm
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
Jong-Hoon Oh, H. Sebastian Seung
NECO
2010
154views more  NECO 2010»
15 years 5 months ago
Role of Homeostasis in Learning Sparse Representations
Neurons in the input layer of primary visual cortex in primates develop edge-like receptive fields. One approach to understanding the emergence of this response is to state that ...
Laurent U. Perrinet
JOCN
2011
80views more  JOCN 2011»
15 years 1 months ago
Neural Changes Associated with Nonspeech Auditory Category Learning Parallel Those of Speech Category Acquisition
■ Native language experience plays a critical role in shaping speech categorization, but the exact mechanisms by which it does so are not well understood. Investigating category...
Ran Liu, Lori L. Holt
ISER
2004
Springer
143views Robotics» more  ISER 2004»
16 years 8 days ago
Imitation Learning Based on Visuo-Somatic Mapping
Abstract. Imitation learning is a powerful approach to humanoid behavior generation, however, the most existing methods assume the availability of the information on the internal s...
Minoru Asada, Masaki Ogino, Shigeo Matsuyama, Jun'...
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...