Reducing Computational Complexity of Neural Networks in Optical Channel Equalization: From Concepts to Implementation

no code implementations • 26 Aug 2022 • Pedro J. Freire, Antonio Napoli, Diego Arguello Ron, Bernhard Spinnler, Michael Anderson, Wolfgang Schairer, Thomas Bex, Nelson Costa, Sergei K. Turitsyn, Jaroslaw E. Prilepsky

In this work, we propose and evaluate a Bayesian optimization-assisted compression, in which the hyperparameters of the compression are chosen to simultaneously reduce complexity and improve performance.

Bayesian Optimization Clustering +2