Pruning Randomly Initialized Neural Networks with Iterative Randomization

17 June 2021

Papers citing "Pruning Randomly Initialized Neural Networks with Iterative Randomization"

7 / 7 papers shown

Title
On Model Compression for Neural Networks: Framework, Algorithm, and Convergence Guarantee Chenyang Li Jihoon Chung Mengnan Du Haimin Wang Xianlian Zhou Bohao Shen 33 1 0 13 Mar 2023
Considering Layerwise Importance in the Lottery Ticket Hypothesis Benjamin Vandersmissen José Oramas 15 1 0 22 Feb 2023
You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets Tianjin Huang Tianlong Chen Meng Fang Vlado Menkovski Jiaxu Zhao ... Yulong Pei D. Mocanu Zhangyang Wang Mykola Pechenizkiy Shiwei Liu GNN 34 14 0 28 Nov 2022
The Combinatorial Brain Surgeon: Pruning Weights That Cancel One Another in Neural Networks Xin Yu Thiago Serra Srikumar Ramalingam Shandian Zhe 34 48 0 09 Mar 2022
Robust Binary Models by Pruning Randomly-initialized Networks Chen Liu Ziqi Zhao Sabine Süsstrunk Mathieu Salzmann TPM AAML MQ 16 4 0 03 Feb 2022
Signing the Supermask: Keep, Hide, Invert Nils Koster O. Grothe Achim Rettinger 23 10 0 31 Jan 2022
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks Torsten Hoefler Dan Alistarh Tal Ben-Nun Nikoli Dryden Alexandra Peste MQ 139 684 0 31 Jan 2021