Oja's rule

Oja's learning rule, or simply Oja's rule, named after Finnish computer scientist Erkki Oja, is a model of how neurons in the brain or in artificial… (More)
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Topic mentions per year

Topic mentions per year

1994-2015
01219942015

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2016
2016
Crossbar arrays of memristive elements are investigated for the implementation of dictionary learning and sparse coding of… (More)
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2012
2012
  • Paul Honeine
  • IEEE Transactions on Pattern Analysis and Machine…
  • 2012
Kernel principal component analysis (kernel-PCA) is an elegant nonlinear extension of one of the most used data analysis and… (More)
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2009
2009
We consider the problem of learning an unknown (overcomplete) basis from data that are generated from unknown and sparse linear… (More)
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2008
2008
We consider the problem of learning an unknown (overcomplete) basis from an unknown sparse linear combination. Introducing the… (More)
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2007
2007
Principal component analysis (PCA) is a widely used technique for data analysis and dimensionality reduction. Eigenvalue… (More)
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2007
2007
A model for unsupervised learning from N {dimensional data is studied. Random training examples are drawn such that the… (More)
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2005
2005
Connectionist networks have been criticized for their inability to represent complex structures with systematicity. That is… (More)
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2000
2000
A learning algorithm for the principal component analysis is developed based on the least-square minimization. The dual learning… (More)
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1997
1997
On-line learning rules for both Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) with Fisher criterion… (More)
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1996
1996
This paper presents an unsupervised learning scheme for initializing the internal representations of feedforward neural networks… (More)
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