Surrogate Lagrangian Relaxation: A Path To Retrain-free Deep Neural Network Pruning

8 April 2023

Caiwen Ding

Papers citing "Surrogate Lagrangian Relaxation: A Path To Retrain-free Deep Neural Network Pruning"

3 / 3 papers shown

Title
Survey on Lagrangian Relaxation for MILP: Importance, Challenges, Historical Review, Recent Advancements, and Opportunities Mikhail A. Bragin 14 11 0 02 Jan 2023
MLP-Mixer: An all-MLP Architecture for Vision Ilya O. Tolstikhin N. Houlsby Alexander Kolesnikov Lucas Beyer Xiaohua Zhai ... Andreas Steiner Daniel Keysers Jakob Uszkoreit Mario Lucic Alexey Dosovitskiy 280 2,606 0 04 May 2021
Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression Yawei Li Shuhang Gu Christoph Mayer Luc Van Gool Radu Timofte 137 189 0 19 Mar 2020