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OptG: Optimizing Gradient-driven Criteria in Network Sparsity

OptG: Optimizing Gradient-driven Criteria in Network Sparsity

Yu-xin Zhang
Mingbao Lin
Mengzhao Chen
Fei Chao
Rongrong Ji
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Papers citing "OptG: Optimizing Gradient-driven Criteria in Network Sparsity"

4 / 4 papers shown
Title
SequentialAttention++ for Block Sparsification: Differentiable Pruning Meets Combinatorial Optimization
SequentialAttention++ for Block Sparsification: Differentiable Pruning Meets Combinatorial Optimization
T. Yasuda
Kyriakos Axiotis
Gang Fu
M. Bateni
Vahab Mirrokni
27
0
0
27 Feb 2024
MaxQ: Multi-Axis Query for N:M Sparsity Network
MaxQ: Multi-Axis Query for N:M Sparsity Network
Jingyang Xiang
Siqi Li
Junhao Chen
Zhuangzhi Chen
Tianxin Huang
Linpeng Peng
Yong-Jin Liu
11
0
0
12 Dec 2023
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks
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
136
679
0
31 Jan 2021
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Andrew G. Howard
Menglong Zhu
Bo Chen
Dmitry Kalenichenko
Weijun Wang
Tobias Weyand
M. Andreetto
Hartwig Adam
3DH
948
20,214
0
17 Apr 2017