ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2008.08316
  4. Cited By
Data-Independent Structured Pruning of Neural Networks via Coresets

Data-Independent Structured Pruning of Neural Networks via Coresets

19 August 2020
Ben Mussay
Dan Feldman
Samson Zhou
Vladimir Braverman
Margarita Osadchy
ArXivPDFHTML

Papers citing "Data-Independent Structured Pruning of Neural Networks via Coresets"

16 / 16 papers shown
Title
Neural Pruning for 3D Scene Reconstruction: Efficient NeRF Acceleration
Neural Pruning for 3D Scene Reconstruction: Efficient NeRF Acceleration
Tianqi Ding
Dawei Xiang
Pablo Rivas
Liang Dong
303
1
0
01 Apr 2025
Parallel Blockwise Knowledge Distillation for Deep Neural Network
  Compression
Parallel Blockwise Knowledge Distillation for Deep Neural Network Compression
Cody Blakeney
Xiaomin Li
Yan Yan
Ziliang Zong
58
40
0
05 Dec 2020
Provable Filter Pruning for Efficient Neural Networks
Provable Filter Pruning for Efficient Neural Networks
Lucas Liebenwein
Cenk Baykal
Harry Lang
Dan Feldman
Daniela Rus
VLM
3DPC
61
140
0
18 Nov 2019
Towards Optimal Structured CNN Pruning via Generative Adversarial
  Learning
Towards Optimal Structured CNN Pruning via Generative Adversarial Learning
Shaohui Lin
Rongrong Ji
Chenqian Yan
Baochang Zhang
Liujuan Cao
QiXiang Ye
Feiyue Huang
David Doermann
CVBM
46
506
0
22 Mar 2019
Coreset-Based Neural Network Compression
Coreset-Based Neural Network Compression
Abhimanyu Dubey
Moitreya Chatterjee
Narendra Ahuja
48
79
0
25 Jul 2018
Data-Dependent Coresets for Compressing Neural Networks with
  Applications to Generalization Bounds
Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds
Cenk Baykal
Lucas Liebenwein
Igor Gilitschenski
Dan Feldman
Daniela Rus
50
79
0
15 Apr 2018
AMC: AutoML for Model Compression and Acceleration on Mobile Devices
AMC: AutoML for Model Compression and Acceleration on Mobile Devices
Yihui He
Ji Lin
Zhijian Liu
Hanrui Wang
Li Li
Song Han
69
1,348
0
10 Feb 2018
Learning Efficient Convolutional Networks through Network Slimming
Learning Efficient Convolutional Networks through Network Slimming
Zhuang Liu
Jianguo Li
Zhiqiang Shen
Gao Huang
Shoumeng Yan
Changshui Zhang
98
2,407
0
22 Aug 2017
ThiNet: A Filter Level Pruning Method for Deep Neural Network
  Compression
ThiNet: A Filter Level Pruning Method for Deep Neural Network Compression
Jian-Hao Luo
Jianxin Wu
Weiyao Lin
40
1,758
0
20 Jul 2017
Channel Pruning for Accelerating Very Deep Neural Networks
Channel Pruning for Accelerating Very Deep Neural Networks
Yihui He
Xiangyu Zhang
Jian Sun
189
2,519
0
19 Jul 2017
Pruning Filters for Efficient ConvNets
Pruning Filters for Efficient ConvNets
Hao Li
Asim Kadav
Igor Durdanovic
H. Samet
H. Graf
3DPC
175
3,687
0
31 Aug 2016
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained
  Quantization and Huffman Coding
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding
Song Han
Huizi Mao
W. Dally
3DGS
203
8,793
0
01 Oct 2015
Learning both Weights and Connections for Efficient Neural Networks
Learning both Weights and Connections for Efficient Neural Networks
Song Han
Jeff Pool
J. Tran
W. Dally
CVBM
247
6,628
0
08 Jun 2015
Fast ConvNets Using Group-wise Brain Damage
Fast ConvNets Using Group-wise Brain Damage
V. Lebedev
Victor Lempitsky
AAML
119
448
0
08 Jun 2015
Exploiting Linear Structure Within Convolutional Networks for Efficient
  Evaluation
Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation
Emily L. Denton
Wojciech Zaremba
Joan Bruna
Yann LeCun
Rob Fergus
FAtt
130
1,682
0
02 Apr 2014
A Unified Framework for Approximating and Clustering Data
A Unified Framework for Approximating and Clustering Data
Dan Feldman
M. Langberg
126
457
0
07 Jun 2011
1