Abstract
The cooperative behaviour of interacting neurons and synapses is studied using models and methods from statistical physics. The competition between training error and entropy can lead to discontinuous properties of neural networks. This is demonstrated for a few examples: Attractor networks, storage by synaptic dilution, learning from examples, generalization of multilayer networks, learning without generalization, specialization, Bayesian estimate of the structure of high dimensional data.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.