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» Learning Overcomplete Representations
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ICASSP
2010
IEEE
15 years 2 months ago
Adaptive compressed sensing - A new class of self-organizing coding models for neuroscience
Sparse coding networks, which utilize unsupervised learning to maximize coding efficiency, have successfully reproduced response properties found in primary visual cortex [1]. Ho...
William K. Coulter, Cristopher J. Hillar, Guy Isle...
JMLR
2006
131views more  JMLR 2006»
15 years 2 months ago
On Representing and Generating Kernels by Fuzzy Equivalence Relations
Kernels are two-placed functions that can be interpreted as inner products in some Hilbert space. It is this property which makes kernels predestinated to carry linear models of l...
Bernhard Moser
145
Voted
JSS
2002
198views more  JSS 2002»
15 years 2 months ago
Automated discovery of concise predictive rules for intrusion detection
This paper details an essential component of a multi-agent distributed knowledge network system for intrusion detection. We describe a distributed intrusion detection architecture...
Guy G. Helmer, Johnny S. Wong, Vasant Honavar, Les...
ML
2002
ACM
163views Machine Learning» more  ML 2002»
15 years 2 months ago
Structural Modelling with Sparse Kernels
A widely acknowledged drawback of many statistical modelling techniques, commonly used in machine learning, is that the resulting model is extremely difficult to interpret. A numb...
Steve R. Gunn, Jaz S. Kandola
NN
2007
Springer
112views Neural Networks» more  NN 2007»
15 years 1 months ago
An augmented CRTRL for complex-valued recurrent neural networks
Real world processes with an “intensity” and “direction” component can be made complex by convenience of representation (vector fields, radar, sonar), and their processin...
Su Lee Goh, Danilo P. Mandic