Structured Pruning is All You Need for Pruning CNNs at Initialization

4 March 2022

Papers citing "Structured Pruning is All You Need for Pruning CNNs at Initialization"

8 / 8 papers shown

Title
Rapid Deployment of DNNs for Edge Computing via Structured Pruning at Initialization Bailey J. Eccles Leon Wong Blesson Varghese 33 2 0 22 Apr 2024
DNNShifter: An Efficient DNN Pruning System for Edge Computing Bailey J. Eccles Philip Rodgers Peter Kilpatrick I. Spence Blesson Varghese 32 15 0 13 Sep 2023
Towards Optimal Compression: Joint Pruning and Quantization Ben Zandonati Glenn Bucagu Adrian Alan Pol M. Pierini Olya Sirkin Tal Kopetz MQ 17 2 0 15 Feb 2023
AcceRL: Policy Acceleration Framework for Deep Reinforcement Learning Hongjie Zhang OffRL 13 0 0 28 Nov 2022
Symmetry Structured Convolutional Neural Networks K. D. G. Maduranga Vasily Zadorozhnyy Qiang Ye 14 3 0 03 Mar 2022
What is the State of Neural Network Pruning? Davis W. Blalock Jose Javier Gonzalez Ortiz Jonathan Frankle John Guttag 183 1,027 0 06 Mar 2020
Comparing Rewinding and Fine-tuning in Neural Network Pruning Alex Renda Jonathan Frankle Michael Carbin 222 382 0 05 Mar 2020
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 948 20,549 0 17 Apr 2017