Deepest Neural Networks

Raúl Rojas – 2017

This paper shows that a long chain of perceptrons (that is, a multilayer perceptron, or MLP, with many hidden layers of width one) can be a universal classifier. The classification procedure is not necessarily computationally efficient, but the technique throws some light on the kind of computations possible with narrow and deep MLPs.

Titel
Deepest Neural Networks
Verfasser
Schlagwörter
Neural Networks, Neural and Evolutionary Computing, Learning
Datum
2017-07
Erschienen in
Cornell University Library
Größe oder Länge
9 pages