2022
Depth Pruning with Auxiliary Networks for Tinyml
ICASSP 2022accepted
Pruning is a neural network optimization technique that sacrifices accuracy in exchange for lower computational requirements. Pruning has been useful when working with extremely constrained environments in tinyML. Unfortunately, special hardware requirements and limited study on its effectiveness on…