no code implementations • 26 Jan 2021 • Thomas Gebhart, Udit Saxena, Paul Schrater
A number of recent approaches have been proposed for pruning neural network parameters at initialization with the goal of reducing the size and computational burden of models while minimally affecting their training dynamics and generalization performance.
