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Model compression as constrained optimization, with application to
  neural nets. Part I: general framework

Model compression as constrained optimization, with application to neural nets. Part I: general framework

5 July 2017
Miguel Á. Carreira-Perpiñán
    MQ
ArXiv (abs)PDFHTML

Papers citing "Model compression as constrained optimization, with application to neural nets. Part I: general framework"

13 / 13 papers shown
A Discrepancy-Based Perspective on Dataset Condensation
A Discrepancy-Based Perspective on Dataset Condensation
Tong Chen
Raghavendra Selvan
DD
261
0
0
12 Sep 2025
Search-Optimized Quantization in Biomedical Ontology Alignment
Search-Optimized Quantization in Biomedical Ontology AlignmentFrontiers in Artificial Intelligence (Front. Artif. Intell.), 2025
Oussama Bouaggad
Natalia Grabar
MQ
175
0
0
18 Jul 2025
On Model Compression for Neural Networks: Framework, Algorithm, and
  Convergence Guarantee
On Model Compression for Neural Networks: Framework, Algorithm, and Convergence Guarantee
Chenyang Li
Jihoon Chung
Mengnan Du
Haimin Wang
Xianlian Zhou
Bohao Shen
211
1
0
13 Mar 2023
A Comprehensive Survey on Model Quantization for Deep Neural Networks in
  Image Classification
A Comprehensive Survey on Model Quantization for Deep Neural Networks in Image ClassificationACM Transactions on Intelligent Systems and Technology (ACM TIST), 2022
Babak Rokh
A. Azarpeyvand
Alireza Khanteymoori
MQ
459
172
0
14 May 2022
When in Doubt, Summon the Titans: Efficient Inference with Large Models
When in Doubt, Summon the Titans: Efficient Inference with Large Models
A. S. Rawat
Manzil Zaheer
A. Menon
Amr Ahmed
Sanjiv Kumar
124
8
0
19 Oct 2021
Model compression as constrained optimization, with application to
  neural nets. Part V: combining compressions
Model compression as constrained optimization, with application to neural nets. Part V: combining compressions
Miguel Á. Carreira-Perpiñán
Yerlan Idelbayev
214
6
0
09 Jul 2021
Going Beyond Classification Accuracy Metrics in Model Compression
Going Beyond Classification Accuracy Metrics in Model Compression
Vinu Joseph
Shoaib Ahmed Siddiqui
Aditya Bhaskara
Ganesh Gopalakrishnan
Saurav Muralidharan
M. Garland
Sheraz Ahmed
Andreas Dengel
184
18
0
03 Dec 2020
A flexible, extensible software framework for model compression based on
  the LC algorithm
A flexible, extensible software framework for model compression based on the LC algorithm
Yerlan Idelbayev
Miguel Á. Carreira-Perpiñán
158
9
0
15 May 2020
A Programmable Approach to Neural Network Compression
A Programmable Approach to Neural Network Compression
Vinu Joseph
Saurav Muralidharan
Animesh Garg
M. Garland
Ganesh Gopalakrishnan
221
10
0
06 Nov 2019
Channel-wise pruning of neural networks with tapering resource
  constraint
Channel-wise pruning of neural networks with tapering resource constraint
A. Kruglov
92
1
0
04 Dec 2018
ProxQuant: Quantized Neural Networks via Proximal Operators
ProxQuant: Quantized Neural Networks via Proximal Operators
Yu Bai
Yu Wang
Edo Liberty
MQ
266
127
0
01 Oct 2018
Blended Coarse Gradient Descent for Full Quantization of Deep Neural
  Networks
Blended Coarse Gradient Descent for Full Quantization of Deep Neural Networks
Penghang Yin
Shuai Zhang
J. Lyu
Stanley Osher
Y. Qi
Jack Xin
MQ
248
67
0
15 Aug 2018
Model compression as constrained optimization, with application to
  neural nets. Part II: quantization
Model compression as constrained optimization, with application to neural nets. Part II: quantization
M. A. Carreira-Perpiñán
Yerlan Idelbayev
MQ
160
39
0
13 Jul 2017
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