WoodFisher: Efficient Second-Order Approximation for Neural Network
Compression

WoodFisher: Efficient Second-Order Approximation for Neural Network Compression

29 April 2020

Sidak Pal Singh

Dan Alistarh

Papers citing "WoodFisher: Efficient Second-Order Approximation for Neural Network Compression"

8 / 8 papers shown

Title
Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Pruning Huan Wang Can Qin Yue Bai Yun Fu 42 20 0 12 Jan 2023
Dual Lottery Ticket Hypothesis Yue Bai Haiquan Wang Zhiqiang Tao Kunpeng Li Yun Fu 37 37 0 08 Mar 2022
Cyclical Pruning for Sparse Neural Networks Suraj Srinivas Andrey Kuzmin Markus Nagel M. V. Baalen Andrii Skliar Tijmen Blankevoort 43 13 0 02 Feb 2022
SAND-mask: An Enhanced Gradient Masking Strategy for the Discovery of Invariances in Domain Generalization Soroosh Shahtalebi Jean-Christophe Gagnon-Audet Touraj Laleh Mojtaba Faramarzi Kartik Ahuja Irina Rish 33 60 0 04 Jun 2021
Lost in Pruning: The Effects of Pruning Neural Networks beyond Test Accuracy Lucas Liebenwein Cenk Baykal Brandon Carter David K Gifford Daniela Rus AAML 42 72 0 04 Mar 2021
Neural Pruning via Growing Regularization Huan Wang Can Qin Yulun Zhang Y. Fu 39 144 0 16 Dec 2020
Learning explanations that are hard to vary Giambattista Parascandolo Alexander Neitz Antonio Orvieto Luigi Gresele Bernhard Schölkopf FAtt 32 179 0 01 Sep 2020
Revisiting Loss Modelling for Unstructured Pruning César Laurent Camille Ballas Thomas George Nicolas Ballas Pascal Vincent 35 14 0 22 Jun 2020