Dense for the Price of Sparse: Improved Performance of Sparsely Initialized Networks via a Subspace Offset

12 February 2021

Papers citing "Dense for the Price of Sparse: Improved Performance of Sparsely Initialized Networks via a Subspace Offset"

5 / 5 papers shown

Title
Pushing the Limits of Sparsity: A Bag of Tricks for Extreme Pruning Andy Li A. Durrant Milan Markovic Lu Yin Georgios Leontidis Tianlong Chen Lu Yin Georgios Leontidis 70 0 0 20 Nov 2024
Navigating Extremes: Dynamic Sparsity in Large Output Spaces Nasib Ullah Erik Schultheis Mike Lasby Yani Andrew Ioannou Rohit Babbar 33 0 0 05 Nov 2024
Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity Shiwei Liu Tianlong Chen Zahra Atashgahi Xiaohan Chen Ghada Sokar Elena Mocanu Mykola Pechenizkiy Zhangyang Wang D. Mocanu OOD 25 49 0 28 Jun 2021
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
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks Lechao Xiao Yasaman Bahri Jascha Narain Sohl-Dickstein S. Schoenholz Jeffrey Pennington 220 348 0 14 Jun 2018