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Structured Bayesian Pruning via Log-Normal Multiplicative Noise

Structured Bayesian Pruning via Log-Normal Multiplicative Noise

20 May 2017
Kirill Neklyudov
Dmitry Molchanov
Arsenii Ashukha
Dmitry Vetrov
    BDL
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Papers citing "Structured Bayesian Pruning via Log-Normal Multiplicative Noise"

34 / 34 papers shown
Title
A Bayesian Interpretation of Adaptive Low-Rank Adaptation
A Bayesian Interpretation of Adaptive Low-Rank Adaptation
Haolin Chen
Philip N. Garner
61
1
0
16 Sep 2024
Cluster Generation via Deep Energy-Based Model
Cluster Generation via Deep Energy-Based Model
A. Y. Artsukevich
S. Lepeshkin
34
0
0
17 Jun 2022
Statistical Guarantees for Approximate Stationary Points of Simple
  Neural Networks
Statistical Guarantees for Approximate Stationary Points of Simple Neural Networks
Mahsa Taheri
Fang Xie
Johannes Lederer
31
0
0
09 May 2022
A Survey on Dropout Methods and Experimental Verification in
  Recommendation
A Survey on Dropout Methods and Experimental Verification in Recommendation
Yongqian Li
Weizhi Ma
C. L. Philip Chen
Hao Fei
Yiqun Liu
Shaoping Ma
Yue Yang
40
10
0
05 Apr 2022
Speedup deep learning models on GPU by taking advantage of efficient
  unstructured pruning and bit-width reduction
Speedup deep learning models on GPU by taking advantage of efficient unstructured pruning and bit-width reduction
Marcin Pietroñ
Dominik Zurek
30
13
0
28 Dec 2021
MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the
  Edge
MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge
Geng Yuan
Xiaolong Ma
Wei Niu
Zhengang Li
Zhenglun Kong
...
Minghai Qin
Bin Ren
Yanzhi Wang
Sijia Liu
Xue Lin
33
89
0
26 Oct 2021
Dynamic Neural Network Architectural and Topological Adaptation and
  Related Methods -- A Survey
Dynamic Neural Network Architectural and Topological Adaptation and Related Methods -- A Survey
Lorenz Kummer
AI4CE
45
0
0
28 Jul 2021
R-Drop: Regularized Dropout for Neural Networks
R-Drop: Regularized Dropout for Neural Networks
Xiaobo Liang
Lijun Wu
Juntao Li
Yue Wang
Qi Meng
Tao Qin
Wei Chen
Hao Fei
Tie-Yan Liu
52
425
0
28 Jun 2021
DiffPrune: Neural Network Pruning with Deterministic Approximate Binary
  Gates and $L_0$ Regularization
DiffPrune: Neural Network Pruning with Deterministic Approximate Binary Gates and L0L_0L0​ Regularization
Yaniv Shulman
46
3
0
07 Dec 2020
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
31
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
Dirichlet Pruning for Neural Network Compression
Dirichlet Pruning for Neural Network Compression
Kamil Adamczewski
Mijung Park
27
3
0
10 Nov 2020
Neural Network Compression Via Sparse Optimization
Neural Network Compression Via Sparse Optimization
Tianyi Chen
Bo Ji
Yixin Shi
Tianyu Ding
Biyi Fang
Sheng Yi
Xiao Tu
36
15
0
10 Nov 2020
Principal Component Networks: Parameter Reduction Early in Training
Principal Component Networks: Parameter Reduction Early in Training
R. Waleffe
Theodoros Rekatsinas
3DPC
19
9
0
23 Jun 2020
Adaptative Inference Cost With Convolutional Neural Mixture Models
Adaptative Inference Cost With Convolutional Neural Mixture Models
Adria Ruiz
Jakob Verbeek
VLM
30
22
0
19 Aug 2019
Bayesian Generative Models for Knowledge Transfer in MRI Semantic
  Segmentation Problems
Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation Problems
Anna Kuzina
Evgenii Egorov
Evgeny Burnaev
MedIm
34
19
0
15 Aug 2019
Importance Estimation for Neural Network Pruning
Importance Estimation for Neural Network Pruning
Pavlo Molchanov
Arun Mallya
Stephen Tyree
I. Frosio
Jan Kautz
3DPC
42
861
0
25 Jun 2019
Compressing RNNs for IoT devices by 15-38x using Kronecker Products
Compressing RNNs for IoT devices by 15-38x using Kronecker Products
Urmish Thakker
Jesse G. Beu
Dibakar Gope
Chu Zhou
Igor Fedorov
Ganesh S. Dasika
Matthew Mattina
27
36
0
07 Jun 2019
Training CNNs with Selective Allocation of Channels
Training CNNs with Selective Allocation of Channels
Jongheon Jeong
Jinwoo Shin
CVBM
41
15
0
11 May 2019
Play and Prune: Adaptive Filter Pruning for Deep Model Compression
Play and Prune: Adaptive Filter Pruning for Deep Model Compression
Pravendra Singh
Vinay Kumar Verma
Piyush Rai
Vinay P. Namboodiri
VLM
33
71
0
11 May 2019
Survey of Dropout Methods for Deep Neural Networks
Survey of Dropout Methods for Deep Neural Networks
Alex Labach
Hojjat Salehinejad
S. Valaee
27
149
0
25 Apr 2019
NIPS - Not Even Wrong? A Systematic Review of Empirically Complete
  Demonstrations of Algorithmic Effectiveness in the Machine Learning and
  Artificial Intelligence Literature
NIPS - Not Even Wrong? A Systematic Review of Empirically Complete Demonstrations of Algorithmic Effectiveness in the Machine Learning and Artificial Intelligence Literature
Franz J. Király
Bilal A. Mateen
R. Sonabend
23
10
0
18 Dec 2018
Structured Pruning of Neural Networks with Budget-Aware Regularization
Structured Pruning of Neural Networks with Budget-Aware Regularization
Carl Lemaire
Andrew Achkar
Pierre-Marc Jodoin
27
92
0
23 Nov 2018
Multi-layer Pruning Framework for Compressing Single Shot MultiBox
  Detector
Multi-layer Pruning Framework for Compressing Single Shot MultiBox Detector
Pravendra Singh
Manikandan Ravikiran
Neeraj Matiyali
Vinay P. Namboodiri
33
21
0
20 Nov 2018
Sparse DNNs with Improved Adversarial Robustness
Sparse DNNs with Improved Adversarial Robustness
Yiwen Guo
Chao Zhang
Changshui Zhang
Yurong Chen
AAML
25
151
0
23 Oct 2018
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural
  Network
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network
Xuanqing Liu
Yao Li
Chongruo Wu
Cho-Jui Hsieh
AAML
OOD
24
171
0
01 Oct 2018
Structured Variational Learning of Bayesian Neural Networks with
  Horseshoe Priors
Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors
S. Ghosh
Jiayu Yao
Finale Doshi-Velez
BDL
UQCV
17
77
0
13 Jun 2018
Energy-Constrained Compression for Deep Neural Networks via Weighted
  Sparse Projection and Layer Input Masking
Energy-Constrained Compression for Deep Neural Networks via Weighted Sparse Projection and Layer Input Masking
Haichuan Yang
Yuhao Zhu
Ji Liu
CVBM
19
36
0
12 Jun 2018
Sampling-Free Variational Inference of Bayesian Neural Networks by
  Variance Backpropagation
Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation
Manuel Haussmann
Fred Hamprecht
M. Kandemir
BDL
33
6
0
19 May 2018
Nonparametric Bayesian Deep Networks with Local Competition
Nonparametric Bayesian Deep Networks with Local Competition
Konstantinos P. Panousis
S. Chatzis
Sergios Theodoridis
BDL
29
32
0
19 May 2018
Variance Networks: When Expectation Does Not Meet Your Expectations
Variance Networks: When Expectation Does Not Meet Your Expectations
Kirill Neklyudov
Dmitry Molchanov
Arsenii Ashukha
Dmitry Vetrov
UQCV
22
23
0
10 Mar 2018
Synthesizing Neural Network Controllers with Probabilistic Model based
  Reinforcement Learning
Synthesizing Neural Network Controllers with Probabilistic Model based Reinforcement Learning
J. A. G. Higuera
David Meger
Gregory Dudek
BDL
22
39
0
06 Mar 2018
Compressing Neural Networks using the Variational Information Bottleneck
Compressing Neural Networks using the Variational Information Bottleneck
Bin Dai
Chen Zhu
David Wipf
MLT
28
179
0
28 Feb 2018
Model Selection in Bayesian Neural Networks via Horseshoe Priors
Model Selection in Bayesian Neural Networks via Horseshoe Priors
S. Ghosh
Finale Doshi-Velez
BDL
39
119
0
29 May 2017
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