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Soft Weight-Sharing for Neural Network Compression

Soft Weight-Sharing for Neural Network Compression

13 February 2017
Karen Ullrich
Edward Meeds
Max Welling
ArXivPDFHTML

Papers citing "Soft Weight-Sharing for Neural Network Compression"

50 / 82 papers shown
Title
Pruning-Based TinyML Optimization of Machine Learning Models for Anomaly Detection in Electric Vehicle Charging Infrastructure
Pruning-Based TinyML Optimization of Machine Learning Models for Anomaly Detection in Electric Vehicle Charging Infrastructure
Fatemeh Dehrouyeh
I. Shaer
S. Nikan
F. Badrkhani Ajaei
Abdallah Shami
66
0
0
19 Mar 2025
Empowering Edge Intelligence: A Comprehensive Survey on On-Device AI Models
Empowering Edge Intelligence: A Comprehensive Survey on On-Device AI Models
Xubin Wang
Zhiqing Tang
Jianxiong Guo
Tianhui Meng
Chenhao Wang
Tian-sheng Wang
Weijia Jia
65
1
0
08 Mar 2025
GenAINet: Enabling Wireless Collective Intelligence via Knowledge Transfer and Reasoning
GenAINet: Enabling Wireless Collective Intelligence via Knowledge Transfer and Reasoning
Han Zou
Qiyang Zhao
Lina Bariah
Yu Tian
M. Bennis
S. Lasaulce
101
12
0
26 Feb 2024
eDKM: An Efficient and Accurate Train-time Weight Clustering for Large
  Language Models
eDKM: An Efficient and Accurate Train-time Weight Clustering for Large Language Models
Minsik Cho
Keivan Alizadeh Vahid
Qichen Fu
Saurabh N. Adya
C. C. D. Mundo
Mohammad Rastegari
Devang Naik
Peter Zatloukal
MQ
29
6
0
02 Sep 2023
Evil from Within: Machine Learning Backdoors through Hardware Trojans
Evil from Within: Machine Learning Backdoors through Hardware Trojans
Alexander Warnecke
Julian Speith
Janka Möller
Konrad Rieck
C. Paar
AAML
24
3
0
17 Apr 2023
Low Rank Optimization for Efficient Deep Learning: Making A Balance
  between Compact Architecture and Fast Training
Low Rank Optimization for Efficient Deep Learning: Making A Balance between Compact Architecture and Fast Training
Xinwei Ou
Zhangxin Chen
Ce Zhu
Yipeng Liu
36
4
0
22 Mar 2023
Efficient Multitask Learning on Resource-Constrained Systems
Efficient Multitask Learning on Resource-Constrained Systems
Yubo Luo
Le Zhang
Zhenyu Wang
S. Nirjon
17
9
0
25 Feb 2023
Efficient and Effective Methods for Mixed Precision Neural Network
  Quantization for Faster, Energy-efficient Inference
Efficient and Effective Methods for Mixed Precision Neural Network Quantization for Faster, Energy-efficient Inference
Deepika Bablani
J. McKinstry
S. K. Esser
R. Appuswamy
D. Modha
MQ
23
4
0
30 Jan 2023
Scaling Deep Networks with the Mesh Adaptive Direct Search algorithm
Scaling Deep Networks with the Mesh Adaptive Direct Search algorithm
Dounia Lakhmiri
Mahdi Zolnouri
V. Nia
C. Tribes
Sébastien Le Digabel
33
0
0
17 Jan 2023
Novel transfer learning schemes based on Siamese networks and synthetic
  data
Novel transfer learning schemes based on Siamese networks and synthetic data
Dominik Stallmann
Philip Kenneweg
Barbara Hammer
18
6
0
21 Nov 2022
Weight Fixing Networks
Weight Fixing Networks
Christopher Subia-Waud
S. Dasmahapatra
MQ
30
2
0
24 Oct 2022
Fast and Low-Memory Deep Neural Networks Using Binary Matrix
  Factorization
Fast and Low-Memory Deep Neural Networks Using Binary Matrix Factorization
Alireza Bordbar
M. Kahaei
MQ
33
0
0
24 Oct 2022
Nonlocal optimization of binary neural networks
Nonlocal optimization of binary neural networks
Amir Khoshaman
Giuseppe Castiglione
C. Srinivasa
18
0
0
05 Apr 2022
Quantization in Layer's Input is Matter
Quantization in Layer's Input is Matter
Daning Cheng
Wenguang Chen
MQ
11
0
0
10 Feb 2022
Reducing Redundancy in the Bottleneck Representation of the Autoencoders
Reducing Redundancy in the Bottleneck Representation of the Autoencoders
Firas Laakom
Jenni Raitoharju
Alexandros Iosifidis
Moncef Gabbouj
33
10
0
09 Feb 2022
Croesus: Multi-Stage Processing and Transactions for Video-Analytics in
  Edge-Cloud Systems
Croesus: Multi-Stage Processing and Transactions for Video-Analytics in Edge-Cloud Systems
Samaa Gazzaz
Vishal Chakraborty
Faisal Nawab
41
10
0
31 Dec 2021
Multi-Glimpse Network: A Robust and Efficient Classification
  Architecture based on Recurrent Downsampled Attention
Multi-Glimpse Network: A Robust and Efficient Classification Architecture based on Recurrent Downsampled Attention
S. Tan
Runpei Dong
Kaisheng Ma
22
2
0
03 Nov 2021
Neural network relief: a pruning algorithm based on neural activity
Neural network relief: a pruning algorithm based on neural activity
Aleksandr Dekhovich
David Tax
M. Sluiter
Miguel A. Bessa
46
10
0
22 Sep 2021
DKM: Differentiable K-Means Clustering Layer for Neural Network
  Compression
DKM: Differentiable K-Means Clustering Layer for Neural Network Compression
Minsik Cho
Keivan Alizadeh Vahid
Saurabh N. Adya
Mohammad Rastegari
42
34
0
28 Aug 2021
A Survey on GAN Acceleration Using Memory Compression Technique
A Survey on GAN Acceleration Using Memory Compression Technique
Dina Tantawy
Mohamed Zahran
A. Wassal
36
8
0
14 Aug 2021
Differentiable Model Compression via Pseudo Quantization Noise
Differentiable Model Compression via Pseudo Quantization Noise
Alexandre Défossez
Yossi Adi
Gabriel Synnaeve
DiffM
MQ
18
47
0
20 Apr 2021
CDFI: Compression-Driven Network Design for Frame Interpolation
CDFI: Compression-Driven Network Design for Frame Interpolation
Tianyu Ding
Luming Liang
Zhihui Zhu
Ilya Zharkov
27
93
0
18 Mar 2021
COIN: COmpression with Implicit Neural representations
COIN: COmpression with Implicit Neural representations
Emilien Dupont
Adam Goliñski
Milad Alizadeh
Yee Whye Teh
Arnaud Doucet
23
223
0
03 Mar 2021
An Information-Theoretic Justification for Model Pruning
An Information-Theoretic Justification for Model Pruning
Berivan Isik
Tsachy Weissman
Albert No
95
35
0
16 Feb 2021
SeReNe: Sensitivity based Regularization of Neurons for Structured
  Sparsity in Neural Networks
SeReNe: Sensitivity based Regularization of Neurons for Structured Sparsity in Neural Networks
Enzo Tartaglione
Andrea Bragagnolo
Francesco Odierna
Attilio Fiandrotti
Marco Grangetto
43
18
0
07 Feb 2021
Rethinking Weight Decay For Efficient Neural Network Pruning
Rethinking Weight Decay For Efficient Neural Network Pruning
Hugo Tessier
Vincent Gripon
Mathieu Léonardon
M. Arzel
T. Hannagan
David Bertrand
26
25
0
20 Nov 2020
Dynamic Hard Pruning of Neural Networks at the Edge of the Internet
Dynamic Hard Pruning of Neural Networks at the Edge of the Internet
Lorenzo Valerio
F. M. Nardini
A. Passarella
R. Perego
25
12
0
17 Nov 2020
LOss-Based SensiTivity rEgulaRization: towards deep sparse neural
  networks
LOss-Based SensiTivity rEgulaRization: towards deep sparse neural networks
Enzo Tartaglione
Andrea Bragagnolo
Attilio Fiandrotti
Marco Grangetto
ODL
UQCV
20
34
0
16 Nov 2020
Dirichlet Pruning for Neural Network Compression
Dirichlet Pruning for Neural Network Compression
Kamil Adamczewski
Mijung Park
27
3
0
10 Nov 2020
Towards an Automatic Analysis of CHO-K1 Suspension Growth in
  Microfluidic Single-cell Cultivation
Towards an Automatic Analysis of CHO-K1 Suspension Growth in Microfluidic Single-cell Cultivation
Dominik Stallmann
Jan Philip Göpfert
Julian Schmitz
A. Grünberger
Barbara Hammer
34
6
0
20 Oct 2020
Pruning Convolutional Filters using Batch Bridgeout
Pruning Convolutional Filters using Batch Bridgeout
Najeeb Khan
Ian Stavness
28
3
0
23 Sep 2020
Abnormal activity capture from passenger flow of elevator based on
  unsupervised learning and fine-grained multi-label recognition
Abnormal activity capture from passenger flow of elevator based on unsupervised learning and fine-grained multi-label recognition
Chunhua Jia
Wenhai Yi
Yu Wu
Hui Huang
Lei Zhang
Leilei Wu
22
2
0
29 Jun 2020
An Overview of Neural Network Compression
An Overview of Neural Network Compression
James OÑeill
AI4CE
45
98
0
05 Jun 2020
Pruning Algorithms to Accelerate Convolutional Neural Networks for Edge
  Applications: A Survey
Pruning Algorithms to Accelerate Convolutional Neural Networks for Edge Applications: A Survey
Jiayi Liu
S. Tripathi
Unmesh Kurup
Mohak Shah
3DPC
MedIm
30
52
0
08 May 2020
Data-Free Network Quantization With Adversarial Knowledge Distillation
Data-Free Network Quantization With Adversarial Knowledge Distillation
Yoojin Choi
Jihwan P. Choi
Mostafa El-Khamy
Jungwon Lee
MQ
27
119
0
08 May 2020
Pruning artificial neural networks: a way to find well-generalizing,
  high-entropy sharp minima
Pruning artificial neural networks: a way to find well-generalizing, high-entropy sharp minima
Enzo Tartaglione
Andrea Bragagnolo
Marco Grangetto
31
11
0
30 Apr 2020
DP-Net: Dynamic Programming Guided Deep Neural Network Compression
DP-Net: Dynamic Programming Guided Deep Neural Network Compression
Dingcheng Yang
Wenjian Yu
Ao Zhou
Haoyuan Mu
G. Yao
Xiaoyi Wang
21
6
0
21 Mar 2020
BiDet: An Efficient Binarized Object Detector
BiDet: An Efficient Binarized Object Detector
Ziwei Wang
Ziyi Wu
Jiwen Lu
Jie Zhou
MQ
62
64
0
09 Mar 2020
Learned Threshold Pruning
Learned Threshold Pruning
K. Azarian
Yash Bhalgat
Jinwon Lee
Tijmen Blankevoort
MQ
28
38
0
28 Feb 2020
Uncertainty Quantification for Sparse Deep Learning
Uncertainty Quantification for Sparse Deep Learning
Yuexi Wang
Veronika Rockova
BDL
UQCV
36
31
0
26 Feb 2020
Communication-Efficient Edge AI: Algorithms and Systems
Communication-Efficient Edge AI: Algorithms and Systems
Yuanming Shi
Kai Yang
Tao Jiang
Jun Zhang
Khaled B. Letaief
GNN
29
327
0
22 Feb 2020
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep
  Learning
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning
Arsenii Ashukha
Alexander Lyzhov
Dmitry Molchanov
Dmitry Vetrov
UQCV
FedML
33
314
0
15 Feb 2020
Resource-Efficient Neural Networks for Embedded Systems
Resource-Efficient Neural Networks for Embedded Systems
Wolfgang Roth
Günther Schindler
Lukas Pfeifenberger
Robert Peharz
Sebastian Tschiatschek
Holger Fröning
Franz Pernkopf
Zoubin Ghahramani
34
47
0
07 Jan 2020
HiLLoC: Lossless Image Compression with Hierarchical Latent Variable
  Models
HiLLoC: Lossless Image Compression with Hierarchical Latent Variable Models
James Townsend
Thomas Bird
Julius Kunze
David Barber
BDL
VLM
21
56
0
20 Dec 2019
TOCO: A Framework for Compressing Neural Network Models Based on
  Tolerance Analysis
TOCO: A Framework for Compressing Neural Network Models Based on Tolerance Analysis
Soroosh Khoram
J. Li
16
1
0
18 Dec 2019
Iteratively Training Look-Up Tables for Network Quantization
Iteratively Training Look-Up Tables for Network Quantization
Fabien Cardinaux
Stefan Uhlich
K. Yoshiyama
Javier Alonso García
Lukas Mauch
Stephen Tiedemann
Thomas Kemp
Akira Nakamura
MQ
27
16
0
12 Nov 2019
DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks
DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks
Simon Wiedemann
H. Kirchhoffer
Stefan Matlage
Paul Haase
Arturo Marbán
...
Ahmed Osman
D. Marpe
H. Schwarz
Thomas Wiegand
Wojciech Samek
49
93
0
27 Jul 2019
Learning Multimodal Fixed-Point Weights using Gradient Descent
Learning Multimodal Fixed-Point Weights using Gradient Descent
Lukas Enderich
Fabian Timm
Lars Rosenbaum
Wolfram Burgard
MQ
17
9
0
16 Jul 2019
Sparse Networks from Scratch: Faster Training without Losing Performance
Sparse Networks from Scratch: Faster Training without Losing Performance
Tim Dettmers
Luke Zettlemoyer
20
334
0
10 Jul 2019
Data-Free Quantization Through Weight Equalization and Bias Correction
Data-Free Quantization Through Weight Equalization and Bias Correction
Markus Nagel
M. V. Baalen
Tijmen Blankevoort
Max Welling
MQ
19
501
0
11 Jun 2019
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