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Batch Normalization: Accelerating Deep Network Training by Reducing
  Internal Covariate Shift
v1v2v3 (latest)

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

11 February 2015
Sergey Ioffe
Christian Szegedy
    OOD
ArXiv (abs)PDFHTML

Papers citing "Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift"

50 / 11,085 papers shown
Title
Ultimate tensorization: compressing convolutional and FC layers alike
Ultimate tensorization: compressing convolutional and FC layers alike
T. Garipov
D. Podoprikhin
Alexander Novikov
Dmitry Vetrov
78
191
0
10 Nov 2016
The Loss Surface of Residual Networks: Ensembles and the Role of Batch
  Normalization
The Loss Surface of Residual Networks: Ensembles and the Role of Batch Normalization
Etai Littwin
Lior Wolf
UQCV
164
15
0
08 Nov 2016
Divide and Conquer Networks
Divide and Conquer Networks
Alex W. Nowak
David Folqué
Joan Bruna
161
21
0
08 Nov 2016
Unrolled Generative Adversarial Networks
Unrolled Generative Adversarial Networks
Luke Metz
Ben Poole
David Pfau
Jascha Narain Sohl-Dickstein
GAN
133
1,005
0
07 Nov 2016
Spatiotemporal Residual Networks for Video Action Recognition
Spatiotemporal Residual Networks for Video Action Recognition
Christoph Feichtenhofer
A. Pinz
Richard P. Wildes
137
719
0
07 Nov 2016
Neural Networks Designing Neural Networks: Multi-Objective
  Hyper-Parameter Optimization
Neural Networks Designing Neural Networks: Multi-Objective Hyper-Parameter Optimization
S. C. Smithson
Guang Yang
W. Gross
B. Meyer
75
90
0
07 Nov 2016
Fixed-point Factorized Networks
Fixed-point Factorized Networks
Peisong Wang
Jian Cheng
MQ
77
43
0
07 Nov 2016
Regularizing CNNs with Locally Constrained Decorrelations
Regularizing CNNs with Locally Constrained Decorrelations
Pau Rodríguez López
Jordi Gonzalez
Guillem Cucurull
J. M. Gonfaus
F. X. Roca
82
133
0
07 Nov 2016
High-Resolution Semantic Labeling with Convolutional Neural Networks
High-Resolution Semantic Labeling with Convolutional Neural Networks
Emmanuel Maggiori
Y. Tarabalka
Guillaume Charpiat
Pierre Alliez
SSeg
70
172
0
07 Nov 2016
DeepSense: A Unified Deep Learning Framework for Time-Series Mobile
  Sensing Data Processing
DeepSense: A Unified Deep Learning Framework for Time-Series Mobile Sensing Data Processing
Shuochao Yao
Shaohan Hu
Yiran Zhao
Aston Zhang
Tarek Abdelzaher
HAIAI4TS
101
627
0
07 Nov 2016
AC-BLSTM: Asymmetric Convolutional Bidirectional LSTM Networks for Text
  Classification
AC-BLSTM: Asymmetric Convolutional Bidirectional LSTM Networks for Text Classification
Depeng Liang
Yongdong Zhang
76
23
0
07 Nov 2016
Entropy-SGD: Biasing Gradient Descent Into Wide Valleys
Entropy-SGD: Biasing Gradient Descent Into Wide Valleys
Pratik Chaudhari
A. Choromańska
Stefano Soatto
Yann LeCun
Carlo Baldassi
C. Borgs
J. Chayes
Levent Sagun
R. Zecchina
ODL
106
775
0
06 Nov 2016
Generative Adversarial Networks as Variational Training of Energy Based
  Models
Generative Adversarial Networks as Variational Training of Energy Based Models
Shuangfei Zhai
Yu Cheng
Rogerio Feris
Zhongfei Zhang
GAN
66
31
0
06 Nov 2016
End-to-end Optimized Image Compression
End-to-end Optimized Image Compression
Johannes Ballé
Valero Laparra
Eero P. Simoncelli
DRL
150
1,724
0
05 Nov 2016
Generative Multi-Adversarial Networks
Generative Multi-Adversarial Networks
Ishan Durugkar
I. Gemp
Sridhar Mahadevan
GAN
99
345
0
05 Nov 2016
Neural Architecture Search with Reinforcement Learning
Neural Architecture Search with Reinforcement Learning
Barret Zoph
Quoc V. Le
531
5,389
0
05 Nov 2016
Topology and Geometry of Half-Rectified Network Optimization
Topology and Geometry of Half-Rectified Network Optimization
C. Freeman
Joan Bruna
254
235
0
04 Nov 2016
Semi-supervised deep learning by metric embedding
Semi-supervised deep learning by metric embedding
Elad Hoffer
Nir Ailon
SSL
68
27
0
04 Nov 2016
Sparsely-Connected Neural Networks: Towards Efficient VLSI
  Implementation of Deep Neural Networks
Sparsely-Connected Neural Networks: Towards Efficient VLSI Implementation of Deep Neural Networks
A. Ardakani
C. Condo
W. Gross
86
42
0
04 Nov 2016
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
489
3,151
0
04 Nov 2016
Deep Information Propagation
Deep Information Propagation
S. Schoenholz
Justin Gilmer
Surya Ganguli
Jascha Narain Sohl-Dickstein
98
371
0
04 Nov 2016
Demystifying ResNet
Demystifying ResNet
Sihan Li
Jiantao Jiao
Yanjun Han
Tsachy Weissman
74
38
0
03 Nov 2016
Deep Learning Approximation for Stochastic Control Problems
Deep Learning Approximation for Stochastic Control Problems
Jiequn Han
E. Weinan
BDL
63
197
0
02 Nov 2016
Neural Machine Translation in Linear Time
Neural Machine Translation in Linear Time
Nal Kalchbrenner
L. Espeholt
Karen Simonyan
Aaron van den Oord
Alex Graves
Koray Kavukcuoglu
AIMat
124
553
0
31 Oct 2016
A deep convolutional neural network using directional wavelets for
  low-dose X-ray CT reconstruction
A deep convolutional neural network using directional wavelets for low-dose X-ray CT reconstruction
Eunhee Kang
Junhong Min
J. C. Ye
OODMedIm
82
770
0
31 Oct 2016
Doubly Convolutional Neural Networks
Doubly Convolutional Neural Networks
Shuangfei Zhai
Yu Cheng
Weining Lu
Zhongfei Zhang
OOD3DV
71
63
0
30 Oct 2016
Compact Deep Convolutional Neural Networks With Coarse Pruning
Compact Deep Convolutional Neural Networks With Coarse Pruning
S. Anwar
Wonyong Sung
3DPC
65
55
0
30 Oct 2016
Improving Sampling from Generative Autoencoders with Markov Chains
Improving Sampling from Generative Autoencoders with Markov Chains
Antonia Creswell
Kai Arulkumaran
Anil Anthony Bharath
BDLSyDaGAN
90
10
0
28 Oct 2016
Learnable Visual Markers
Learnable Visual Markers
O. Grinchuk
V. Lebedev
Victor Lempitsky
GAN
32
13
0
28 Oct 2016
SoundNet: Learning Sound Representations from Unlabeled Video
SoundNet: Learning Sound Representations from Unlabeled Video
Y. Aytar
Carl Vondrick
Antonio Torralba
SSL
168
1,045
0
27 Oct 2016
Learning Scalable Deep Kernels with Recurrent Structure
Learning Scalable Deep Kernels with Recurrent Structure
Maruan Al-Shedivat
A. Wilson
Yunus Saatchi
Zhiting Hu
Eric Xing
BDL
104
105
0
27 Oct 2016
Deep Multi-scale Location-aware 3D Convolutional Neural Networks for
  Automated Detection of Lacunes of Presumed Vascular Origin
Deep Multi-scale Location-aware 3D Convolutional Neural Networks for Automated Detection of Lacunes of Presumed Vascular Origin
Mohsen Ghafoorian
N. Karssemeijer
Tom Heskes
M. Bergkamp
Joost Wissink
...
K. Keizer
F.‐E. Leeuw
Bram van Ginneken
E. Marchiori
B. Platel
MedIm
276
125
0
24 Oct 2016
Small-footprint Highway Deep Neural Networks for Speech Recognition
Small-footprint Highway Deep Neural Networks for Speech Recognition
Liang Lu
Steve Renals
153
16
0
18 Oct 2016
Master's Thesis : Deep Learning for Visual Recognition
Master's Thesis : Deep Learning for Visual Recognition
Rémi Cadène
Nicolas Thome
Matthieu Cord
119
4
0
18 Oct 2016
Towards K-means-friendly Spaces: Simultaneous Deep Learning and
  Clustering
Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering
Bo Yang
Xiao Fu
N. Sidiropoulos
Mingyi Hong
DRL
96
880
0
15 Oct 2016
Amortised MAP Inference for Image Super-resolution
Amortised MAP Inference for Image Super-resolution
C. Sønderby
Jose Caballero
Lucas Theis
Wenzhe Shi
Ferenc Huszár
101
435
0
14 Oct 2016
Removal of Batch Effects using Distribution-Matching Residual Networks
Removal of Batch Effects using Distribution-Matching Residual Networks
Uri Shaham
Kelly P. Stanton
Jun Zhao
Huamin Li
K. Raddassi
Ruth R. Montgomery
Y. Kluger
107
163
0
13 Oct 2016
Towards end-to-end optimisation of functional image analysis pipelines
Towards end-to-end optimisation of functional image analysis pipelines
A. Vilamala
Kristoffer Hougaard Madsen
Lars Kai Hansen
MedIm
35
2
0
13 Oct 2016
Multiple Instance Learning Convolutional Neural Networks for Object
  Recognition
Multiple Instance Learning Convolutional Neural Networks for Object Recognition
Miao Sun
T. Han
Ming-Chang Liu
Ahmad Khodayari-Rostamabad
SSL
78
47
0
11 Oct 2016
Very Deep Convolutional Networks for End-to-End Speech Recognition
Very Deep Convolutional Networks for End-to-End Speech Recognition
Yu Zhang
William Chan
Navdeep Jaitly
AI4TS
101
412
0
10 Oct 2016
Generative Adversarial Nets from a Density Ratio Estimation Perspective
Generative Adversarial Nets from a Density Ratio Estimation Perspective
Masatoshi Uehara
Issei Sato
Masahiro Suzuki
Kotaro Nakayama
Y. Matsuo
GAN
97
104
0
10 Oct 2016
Deep Pyramidal Residual Networks
Deep Pyramidal Residual Networks
Dongyoon Han
Jiwhan Kim
Junmo Kim
136
694
0
10 Oct 2016
Impatient DNNs - Deep Neural Networks with Dynamic Time Budgets
Impatient DNNs - Deep Neural Networks with Dynamic Time Budgets
Manuel Amthor
E. Rodner
Joachim Denzler
110
17
0
10 Oct 2016
Learning Spatial-Semantic Context with Fully Convolutional Recurrent
  Network for Online Handwritten Chinese Text Recognition
Learning Spatial-Semantic Context with Fully Convolutional Recurrent Network for Online Handwritten Chinese Text Recognition
Zecheng Xie
Zenghui Sun
Lianwen Jin
Hao Ni
Terry Lyons
118
124
0
09 Oct 2016
Crafting GBD-Net for Object Detection
Crafting GBD-Net for Object Detection
Xingyu Zeng
Wanli Ouyang
Junjie Yan
Hongsheng Li
Tong Xiao
...
Yucong Zhou
Binh Yang
Zhe Wang
Hui Zhou
Xiaogang Wang
ObjD
84
138
0
08 Oct 2016
Xception: Deep Learning with Depthwise Separable Convolutions
Xception: Deep Learning with Depthwise Separable Convolutions
François Chollet
MDEBDLPINN
1.5K
14,648
0
07 Oct 2016
Learning Grimaces by Watching TV
Learning Grimaces by Watching TV
Samuel Albanie
Andrea Vedaldi
CVBM
48
24
0
07 Oct 2016
QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding
QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding
Dan Alistarh
Demjan Grubic
Jerry Li
Ryota Tomioka
Milan Vojnović
MQ
84
421
0
07 Oct 2016
Multiple Regularizations Deep Learning for Paddy Growth Stages
  Classification from LANDSAT-8
Multiple Regularizations Deep Learning for Paddy Growth Stages Classification from LANDSAT-8
Ines Heidieni Ikasari
Vina Ayumi
M. I. Fanany
S. Mulyono
44
25
0
06 Oct 2016
Ischemic Stroke Identification Based on EEG and EOG using 1D
  Convolutional Neural Network and Batch Normalization
Ischemic Stroke Identification Based on EEG and EOG using 1D Convolutional Neural Network and Batch Normalization
Endang Purnama Giri
M. I. Fanany
A. M. Arymurthy
75
57
0
06 Oct 2016
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