Generalization in Interactive Networks: The Benefits of Inhibitory Competition and Hebbian Learning
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Publication:2723303
DOI10.1162/08997660152002834zbMath0963.68643DBLPjournals/neco/OReilly01OpenAlexW2153758134WikidataQ34270227 ScholiaQ34270227MaRDI QIDQ2723303
Publication date: 5 July 2001
Published in: Neural Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1162/08997660152002834
Learning and adaptive systems in artificial intelligence (68T05) Computing methodologies and applications (68U99)
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Cites Work
- Dynamics and architecture for neural computation
- A simplified neuron model as a principal component analyzer
- Regularization Algorithms for Learning That Are Equivalent to Multilayer Networks
- A Simple Neural Network Exhibiting Selective Activation of Neuronal Ensembles: From Winner-Take-All to Winners-Share-All
- Neural networks and physical systems with emergent collective computational abilities.
- Neurons with graded response have collective computational properties like those of two-state neurons.
- On the Uniform Convergence of Relative Frequencies of Events to Their Probabilities
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