ECCV 2020poster157 citations
DHP: Differentiable Meta Pruning via HyperNetworks
Yawei Li, Shuhang Gu, Kai Zhang, Luc Van Gool, Radu Timofte
Abstract
Network pruning has been the driving force for the acceleration of neural networks and the alleviation of model storage/transmission burden. With the advent of AutoML and neural architecture search (NAS), pruning has become topical with automatic mechanism and searching based architecture optimization. Yet, current automatic designs rely on either reinforcement learning or evolutionary algorithm. Due to the non-differentiability of those algorithms, the pruning algorithm needs a long searching stage before reaching the convergence.
BibTeX
@inproceedings{eccv2020_dhpdifferentiabl,
title = {DHP: Differentiable Meta Pruning via HyperNetworks},
author = {Yawei Li and Shuhang Gu and Kai Zhang and Luc Van Gool and Radu Timofte},
booktitle = {ECCV 2020},
year = {2020}
}