Can I read Models, Networks and Algorithmic Complexity on EtoBox?

Models, Networks and Algorithmic Complexity by Ruffini, Giulio is a scholarly article available to read on EtoBox.

What is Models, Networks and Algorithmic Complexity about?

I aim to show that models, classification or generating functions, invariances and datasets are algorithmically equivalent concepts once properly defined, and provide some concrete examples of them. I then show that a) neural networks (NNs) of different kinds can be seen to implement models, b) that perturbations of inputs and nodes in NNs trained to optimally implement simple models propagate strongly, c) that there is a framework in which recurrent, deep and shallow networks can be seen to fall into a descriptive power hierarchy in agreement with notions from the theory of recursive functions. The motivation for these definitions and following analysis lies in the context of cognitive neuroscience, and in particular in Ruffini (2016), where the concept of model is used extensively, as is the concept of algorithmic complexity.

Author

Ruffini, Giulio

Published

2016

Language

EN