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Variational Dropout Sparsifies Deep Neural Networks
International Conference on Machine Learning (ICML), 2017
19 January 2017
Dmitry Molchanov
Arsenii Ashukha
Dmitry Vetrov
BDL
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Papers citing
"Variational Dropout Sparsifies Deep Neural Networks"
50 / 481 papers shown
Title
Bayesian Model Selection, the Marginal Likelihood, and Generalization
International Conference on Machine Learning (ICML), 2022
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400
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0
23 Feb 2022
Sparsity Winning Twice: Better Robust Generalization from More Efficient Training
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Zhenyu Zhang
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Haoyu Ma
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OOD
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299
52
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20 Feb 2022
Modeling Human Exploration Through Resource-Rational Reinforcement Learning
Neural Information Processing Systems (NeurIPS), 2022
Marcel Binz
Eric Schulz
162
19
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27 Jan 2022
Adaptive Activation-based Structured Pruning
Kaiqi Zhao
Animesh Jain
Ming Zhao
268
5
0
21 Jan 2022
Automatic Sparse Connectivity Learning for Neural Networks
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022
Zhimin Tang
Linkai Luo
Bike Xie
Yiyu Zhu
Rujie Zhao
Lvqing Bi
Chao Lu
231
46
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13 Jan 2022
Recursive Least Squares for Training and Pruning Convolutional Neural Networks
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Chunyuan Zhang
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182
1
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13 Jan 2022
Towards Lightweight Neural Animation : Exploration of Neural Network Pruning in Mixture of Experts-based Animation Models
VISIGRAPP (VISIGRAPP), 2022
Antoine Maiorca
Nathan Hubens
S. Laraba
Thierry Dutoit
163
3
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11 Jan 2022
Sparse Super-Regular Networks
International Conference on Machine Learning and Applications (ICMLA), 2019
Andrew W. E. McDonald
A. Shokoufandeh
166
5
0
04 Jan 2022
Automatic Mixed-Precision Quantization Search of BERT
International Joint Conference on Artificial Intelligence (IJCAI), 2021
Changsheng Zhao
Ting Hua
Yilin Shen
Qian Lou
Hongxia Jin
MQ
147
25
0
30 Dec 2021
Speedup deep learning models on GPU by taking advantage of efficient unstructured pruning and bit-width reduction
Journal of Computer Science (JCS), 2021
Marcin Pietroñ
Dominik Zurek
146
17
0
28 Dec 2021
Probabilistic Approach for Road-Users Detection
Gledson Melotti
Weihao Lu
Pedro Conde
Dezong Zhao
A. Asvadi
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C. Premebida
307
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02 Dec 2021
How Well Do Sparse Imagenet Models Transfer?
Computer Vision and Pattern Recognition (CVPR), 2021
Eugenia Iofinova
Alexandra Peste
Mark Kurtz
Dan Alistarh
357
49
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26 Nov 2021
Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma Distributions
Neural Information Processing Systems (NeurIPS), 2021
Huan Ma
Zongbo Han
Changqing Zhang
Huazhu Fu
Qiufeng Wang
Q. Hu
EDL
UQCV
232
55
0
11 Nov 2021
Variational Multi-Task Learning with Gumbel-Softmax Priors
Neural Information Processing Systems (NeurIPS), 2021
Jiayi Shen
Xiantong Zhen
M. Worring
Ling Shao
138
35
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09 Nov 2021
MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge
Geng Yuan
Xiaolong Ma
Wei Niu
Zhengang Li
Zhenglun Kong
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Minghai Qin
Bin Ren
Yanzhi Wang
Sijia Liu
Xue Lin
342
113
0
26 Oct 2021
Exploring Gradient Flow Based Saliency for DNN Model Compression
ACM Multimedia (ACM MM), 2021
Xinyu Liu
Baopu Li
Daming Gao
Yixuan Yuan
FAtt
121
9
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24 Oct 2021
Probabilistic fine-tuning of pruning masks and PAC-Bayes self-bounded learning
Soufiane Hayou
Bo He
Gintare Karolina Dziugaite
136
2
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22 Oct 2021
Joint Channel and Weight Pruning for Model Acceleration on Moblie Devices
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Xi Sheryl Zhang
Wentao Zhu
Jiaxing Wang
Sen Yang
Ji Liu
Jian Cheng
185
2
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15 Oct 2021
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Pruned Neural Networks
Shuai Zhang
Meng Wang
Sijia Liu
Pin-Yu Chen
Jinjun Xiong
UQCV
MLT
174
13
0
12 Oct 2021
Mining the Weights Knowledge for Optimizing Neural Network Structures
Mengqiao Han
Xiabi Liu
Zhaoyang Hai
Xin Duan
102
1
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11 Oct 2021
A study of the robustness of raw waveform based speaker embeddings under mismatched conditions
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2021
Ge Zhu
Frank Cwitkowitz
Z. Duan
214
3
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08 Oct 2021
GNN is a Counter? Revisiting GNN for Question Answering
Kuan-Chieh Wang
Yuyu Zhang
Diyi Yang
Le Song
Tao Qin
LMTD
159
36
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07 Oct 2021
Powerpropagation: A sparsity inducing weight reparameterisation
Jonathan Richard Schwarz
Siddhant M. Jayakumar
Razvan Pascanu
P. Latham
Yee Whye Teh
337
57
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01 Oct 2021
Deep Neural Compression Via Concurrent Pruning and Self-Distillation
J. Ó. Neill
Sourav Dutta
H. Assem
VLM
127
5
0
30 Sep 2021
Neural network relief: a pruning algorithm based on neural activity
Machine-mediated learning (ML), 2021
Aleksandr Dekhovich
David Tax
M. Sluiter
Miguel A. Bessa
237
14
0
22 Sep 2021
On the Compression of Neural Networks Using
ℓ
0
\ell_0
ℓ
0
-Norm Regularization and Weight Pruning
Neural Networks (NN), 2021
F. Oliveira
E. Batista
R. Seara
137
13
0
10 Sep 2021
Quantization of Generative Adversarial Networks for Efficient Inference: a Methodological Study
International Conference on Pattern Recognition (ICPR), 2021
Pavel Andreev
Alexander Fritzler
Dmitry Vetrov
MQ
90
15
0
31 Aug 2021
Layer-wise Model Pruning based on Mutual Information
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021
Chun Fan
Jiwei Li
Xiang Ao
Leilei Gan
Yuxian Meng
Xiaofei Sun
134
22
0
28 Aug 2021
Layer Adaptive Node Selection in Bayesian Neural Networks: Statistical Guarantees and Implementation Details
Neural Networks (NN), 2021
Sanket Jantre
Shrijita Bhattacharya
T. Maiti
BDL
226
17
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25 Aug 2021
Learning Sparse Analytic Filters for Piano Transcription
Frank Cwitkowitz
M. Heydari
Z. Duan
262
2
0
23 Aug 2021
Explaining Bayesian Neural Networks
Kirill Bykov
Marina M.-C. Höhne
Adelaida Creosteanu
Klaus-Robert Muller
Frederick Klauschen
Shinichi Nakajima
Matthias Kirchler
BDL
AAML
320
29
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23 Aug 2021
Differentiable Subset Pruning of Transformer Heads
Transactions of the Association for Computational Linguistics (TACL), 2021
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Robert Bamler
Mrinmaya Sachan
286
63
0
10 Aug 2021
Pruning Ternary Quantization
Danyang Liu
Xiangshan Chen
Jie Fu
Chen Ma
Xue Liu
MQ
332
0
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23 Jul 2021
LANA: Latency Aware Network Acceleration
Pavlo Molchanov
Jimmy Hall
Hongxu Yin
Jan Kautz
Nicolò Fusi
Arash Vahdat
281
11
0
12 Jul 2021
HEMP: High-order Entropy Minimization for neural network comPression
Enzo Tartaglione
Stéphane Lathuilière
Attilio Fiandrotti
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Marco Grangetto
MQ
132
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12 Jul 2021
Connectivity Matters: Neural Network Pruning Through the Lens of Effective Sparsity
Artem Vysogorets
Julia Kempe
187
28
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05 Jul 2021
One-Cycle Pruning: Pruning ConvNets Under a Tight Training Budget
Nathan Hubens
M. Mancas
B. Gosselin
Marius Preda
T. Zaharia
196
7
0
05 Jul 2021
Dep-
L
0
L_0
L
0
: Improving
L
0
L_0
L
0
-based Network Sparsification via Dependency Modeling
Yang Li
Shihao Ji
105
1
0
30 Jun 2021
R-Drop: Regularized Dropout for Neural Networks
Neural Information Processing Systems (NeurIPS), 2021
Xiaobo Liang
Lijun Wu
Juntao Li
Yue Wang
Qi Meng
Tao Qin
Wei Chen
Hao Fei
Tie-Yan Liu
253
506
0
28 Jun 2021
A Construction Kit for Efficient Low Power Neural Network Accelerator Designs
Petar Jokic
E. Azarkhish
Andrea Bonetti
M. Pons
S. Emery
Luca Benini
167
5
0
24 Jun 2021
AC/DC: Alternating Compressed/DeCompressed Training of Deep Neural Networks
Alexandra Peste
Eugenia Iofinova
Adrian Vladu
Dan Alistarh
AI4CE
552
76
0
23 Jun 2021
Dangers of Bayesian Model Averaging under Covariate Shift
Neural Information Processing Systems (NeurIPS), 2021
Pavel Izmailov
Patrick K. Nicholson
Sanae Lotfi
A. Wilson
OOD
UQCV
BDL
317
48
0
22 Jun 2021
Sparse Training via Boosting Pruning Plasticity with Neuroregeneration
Neural Information Processing Systems (NeurIPS), 2021
Shiwei Liu
Tianlong Chen
Xiaohan Chen
Zahra Atashgahi
Lu Yin
Huanyu Kou
Li Shen
Mykola Pechenizkiy
Zinan Lin
Decebal Constantin Mocanu
255
133
0
19 Jun 2021
NoiseGrad: Enhancing Explanations by Introducing Stochasticity to Model Weights
AAAI Conference on Artificial Intelligence (AAAI), 2021
Kirill Bykov
Anna Hedström
Shinichi Nakajima
Marina M.-C. Höhne
FAtt
213
40
0
18 Jun 2021
Pruning Randomly Initialized Neural Networks with Iterative Randomization
Daiki Chijiwa
Shin'ya Yamaguchi
Yasutoshi Ida
Kenji Umakoshi
T. Inoue
131
28
0
17 Jun 2021
Evaluating the Robustness of Bayesian Neural Networks Against Different Types of Attacks
Yutian Pang
Sheng Cheng
Jueming Hu
Yongming Liu
AAML
175
12
0
17 Jun 2021
CODA: Constructivism Learning for Instance-Dependent Dropout Architecture Construction
Xiaoli Li
111
0
0
15 Jun 2021
The Flip Side of the Reweighted Coin: Duality of Adaptive Dropout and Regularization
Neural Information Processing Systems (NeurIPS), 2021
Daniel LeJeune
Hamid Javadi
Richard G. Baraniuk
244
8
0
14 Jun 2021
Top-KAST: Top-K Always Sparse Training
Neural Information Processing Systems (NeurIPS), 2021
Siddhant M. Jayakumar
Razvan Pascanu
Jack W. Rae
Simon Osindero
Erich Elsen
314
106
0
07 Jun 2021
Evidential Turing Processes
International Conference on Learning Representations (ICLR), 2021
M. Kandemir
Abdullah Akgul
Manuel Haussmann
Gözde B. Ünal
EDL
UQCV
BDL
159
10
0
02 Jun 2021
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