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Understanding Sparse Neural Networks from their Topology via Multipartite Graph Representations

26 May 2023

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Papers citing "Understanding Sparse Neural Networks from their Topology via Multipartite Graph Representations"

22 / 22 papers shown

Title
Zeroth-Order Adaptive Neuron Alignment Based Pruning without Re-Training Elia Cunegatti Leonardo Lucio Custode Giovanni Iacca 151 0 0 11 Nov 2024
Why Random Pruning Is All We Need to Start Sparse Advait Gadhikar Sohom Mukherjee R. Burkholz 96 21 0 05 Oct 2022
Rare Gems: Finding Lottery Tickets at Initialization Kartik K. Sreenivasan Jy-yong Sohn Liu Yang Matthew Grinde Alliot Nagle Hongyi Wang Eric P. Xing Kangwook Lee Dimitris Papailiopoulos 52 42 0 24 Feb 2022
The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training Shiwei Liu Tianlong Chen Xiaohan Chen Li Shen Decebal Constantin Mocanu Zhangyang Wang Mykola Pechenizkiy 86 113 0 05 Feb 2022
Leveraging the Graph Structure of Neural Network Training Dynamics Fatemeh Vahedian Ruiyu Li Puja Trivedi Di Jin Danai Koutra AI4CE GNN 56 3 0 09 Nov 2021
Connectivity Matters: Neural Network Pruning Through the Lens of Effective Sparsity Artem Vysogorets Julia Kempe 102 22 0 05 Jul 2021
Graph Structure of Neural Networks Jiaxuan You J. Leskovec Kaiming He Saining Xie GNN 84 141 0 13 Jul 2020
Progressive Skeletonization: Trimming more fat from a network at initialization Pau de Jorge Amartya Sanyal Harkirat Singh Behl Philip Torr Grégory Rogez P. Dokania 105 95 0 16 Jun 2020
Hcore-Init: Neural Network Initialization based on Graph Degeneracy Stratis Limnios George Dasoulas D. Thilikos Michalis Vazirgiannis GNN 19 8 0 16 Apr 2020
Proving the Lottery Ticket Hypothesis: Pruning is All You Need Eran Malach Gilad Yehudai Shai Shalev-Shwartz Ohad Shamir 112 276 0 03 Feb 2020
What's Hidden in a Randomly Weighted Neural Network? Vivek Ramanujan Mitchell Wortsman Aniruddha Kembhavi Ali Farhadi Mohammad Rastegari 68 362 0 29 Nov 2019
Rigging the Lottery: Making All Tickets Winners Utku Evci Trevor Gale Jacob Menick Pablo Samuel Castro Erich Elsen 201 607 0 25 Nov 2019
Sparse Networks from Scratch: Faster Training without Losing Performance Tim Dettmers Luke Zettlemoyer 149 340 0 10 Jul 2019
Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask Hattie Zhou Janice Lan Rosanne Liu J. Yosinski UQCV 74 389 0 03 May 2019
Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology Bastian Rieck Matteo Togninalli Christian Bock Michael Moor Max Horn Thomas Gumbsch Karsten Borgwardt 82 111 0 23 Dec 2018
SNIP: Single-shot Network Pruning based on Connection Sensitivity Namhoon Lee Thalaiyasingam Ajanthan Philip Torr VLM 274 1,212 0 04 Oct 2018
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks Jonathan Frankle Michael Carbin 293 3,489 0 09 Mar 2018
To prune, or not to prune: exploring the efficacy of pruning for model compression Michael Zhu Suyog Gupta 202 1,282 0 05 Oct 2017
A Downsampled Variant of ImageNet as an Alternative to the CIFAR datasets P. Chrabaszcz I. Loshchilov Frank Hutter SSeg OOD 177 649 0 27 Jul 2017
Scalable Training of Artificial Neural Networks with Adaptive Sparse Connectivity inspired by Network Science Decebal Constantin Mocanu Elena Mocanu Peter Stone Phuong H. Nguyen M. Gibescu A. Liotta 187 637 0 15 Jul 2017
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 471 43,357 0 11 Feb 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He Xinming Zhang Shaoqing Ren Jian Sun VLM 358 18,661 0 06 Feb 2015