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» Unsupervised learning in neural computation
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ICCV
2009
IEEE
13 years 6 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
ICES
2003
Springer
111views Hardware» more  ICES 2003»
14 years 2 months ago
Spiking Neural Networks for Reconfigurable POEtic Tissue
Abstract. Vertebrate and most invertebrate organisms interact with their environment through processes of adaptation and learning. Such processes are generally controlled by comple...
Jan Eriksson, Oriol Torres, Andrew Mitchell, Gayle...
IJON
2006
56views more  IJON 2006»
13 years 8 months ago
A computational model of anterior intraparietal (AIP) neurons
The monkey parietal anterior intraparietal area (AIP) is part of the grasp planning and execution circuit which contains neurons that encode object features relevant for grasping,...
Erhan Oztop, Hiroshi Imamizu, Gordon Cheng, Mitsuo...
CVPR
2012
IEEE
11 years 11 months ago
Image denoising: Can plain neural networks compete with BM3D?
Image denoising can be described as the problem of mapping from a noisy image to a noise-free image. The best currently available denoising methods approximate this mapping with c...
Harold Christopher Burger, Christian J. Schuler, S...
ICPR
2004
IEEE
14 years 10 months ago
Supervised Nonparametric Information Theoretic Classification
In this paper, supervised nonparametric information theoretic classification (ITC) is introduced. Its principle relies on the likelihood of a data sample of transmitting its class...
Cédric Archambeau, Jean-Philippe Thiran, Mi...