Instantaneously Trained Neural Networks

01/30/2006 ∙ by Abhilash Ponnath, et al. ∙ 0 ∙ share

This paper presents a review of instantaneously trained neural networks (ITNNs). These networks trade learning time for size and, in the basic model, a new hidden node is created for each training sample. Various versions of the corner-classification family of ITNNs, which have found applications in artificial intelligence (AI), are described. Implementation issues are also considered.

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Instantaneously Trained Neural Networks

Authors

Review of Deep Learning

Neurocontrol methods review

The Future of Neural Networks

Adaptive Wind Driven Optimization Trained Artificial Neural Networks

Parametrical Neural Networks and Some Other Similar Architectures

Playing magic tricks to deep neural networks untangles human deception

Fast-DENSER++: Evolving Fully-Trained Deep Artificial Neural Networks

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