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1712.00409
Cited By
Deep Learning Scaling is Predictable, Empirically
1 December 2017
Joel Hestness
Sharan Narang
Newsha Ardalani
G. Diamos
Heewoo Jun
Hassan Kianinejad
Md. Mostofa Ali Patwary
Yang Yang
Yanqi Zhou
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Papers citing
"Deep Learning Scaling is Predictable, Empirically"
50 / 386 papers shown
Title
Learning Transferable Visual Models From Natural Language Supervision
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Efficient Client Contribution Evaluation for Horizontal Federated Learning
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Xinghua Zhu
Jianzong Wang
Jing Xiao
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26 Feb 2021
Explaining Neural Scaling Laws
Yasaman Bahri
Ethan Dyer
Jared Kaplan
Jaehoon Lee
Utkarsh Sharma
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12 Feb 2021
Learning Curve Theory
Marcus Hutter
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08 Feb 2021
An Update on a Progressively Expanded Database for Automated Lung Sound Analysis
Fu-Shun Hsu
Shang-Ran Huang
Chien-Wen Huang
Yuan-Ren Cheng
Chun-Chieh Chen
Jack Hsiao
Chung-Wei Chen
F. Lai
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08 Feb 2021
Network Support for High-performance Distributed Machine Learning
F. Malandrino
C. Chiasserini
Nuria Molner
Antonio de la Oliva
52
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05 Feb 2021
Benchmarking of eight recurrent neural network variants for breath phase and adventitious sound detection on a self-developed open-access lung sound database-HF_Lung_V1
Fu-Shun Hsu
Shang-Ran Huang
Chien-Wen Huang
Chao-Jung Huang
Yuan-Ren Cheng
...
Yi-Lin Wu
Tzu-Ling Tzeng
Ching-Ting Tseng
Yi-Tsun Chen
F. Lai
43
53
0
05 Feb 2021
E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials
Simon L. Batzner
Albert Musaelian
Lixin Sun
Mario Geiger
J. Mailoa
M. Kornbluth
N. Molinari
Tess E. Smidt
Boris Kozinsky
233
1,240
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08 Jan 2021
A Clinical Evaluation of a Low-Cost Strain Gauge Respiration Belt and Machine Learning to Detect Sleep Apnea
Stein Kristiansen
K. Nikolaidis
T. Plagemann
V. Goebel
G. Traaen
...
S. Steinshamn
C. Bendz
O. Anfinsen
L. Gullestad
Harriet Akre
16
14
0
07 Jan 2021
Perspective: A Phase Diagram for Deep Learning unifying Jamming, Feature Learning and Lazy Training
Mario Geiger
Leonardo Petrini
M. Wyart
DRL
31
11
0
30 Dec 2020
Analysis of the Scalability of a Deep-Learning Network for Steganography "Into the Wild"
Hugo Ruiz
Marc Chaumont
Mehdi Yedroudj
A. Amara
Frédéric Comby
Gérard Subsol
29
9
0
29 Dec 2020
*-CFQ: Analyzing the Scalability of Machine Learning on a Compositional Task
Dmitry Tsarkov
Tibor Tihon
Nathan Scales
Nikola Momchev
Danila Sinopalnikov
Nathanael Scharli
18
17
0
15 Dec 2020
Generalization bounds for deep learning
Guillermo Valle Pérez
A. Louis
BDL
13
44
0
07 Dec 2020
Learning Curves for Drug Response Prediction in Cancer Cell Lines
A. Partin
Thomas Brettin
Yvonne A. Evrard
Yitan Zhu
H. Yoo
...
Austin R. Clyde
Maulik Shukla
Michael Fonstein
J. Doroshow
Rick L. Stevens
18
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25 Nov 2020
Video Big Data Analytics in the Cloud: A Reference Architecture, Survey, Opportunities, and Open Research Issues
A. Alam
I. Ullah
Young-Koo Lee
42
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16 Nov 2020
Video Big Data Analytics in the Cloud: Research Issues and Challenges
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Muhammad Numan Khan
Tariq Habib Afridi
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18
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05 Nov 2020
Understanding Capacity-Driven Scale-Out Neural Recommendation Inference
Michael Lui
Yavuz Yetim
Özgür Özkan
Zhuoran Zhao
Shin-Yeh Tsai
Carole-Jean Wu
Mark Hempstead
GNN
BDL
LRM
22
51
0
04 Nov 2020
CopyPaste: An Augmentation Method for Speech Emotion Recognition
R. Pappagari
Jesús Villalba
Piotr Żelasko
Laureano Moro Velázquez
Najim Dehak
19
39
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27 Oct 2020
Are wider nets better given the same number of parameters?
A. Golubeva
Behnam Neyshabur
Guy Gur-Ari
27
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The De-democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Research
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Muntasir Wahed
25
106
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22 Oct 2020
Deep Learning is Singular, and That's Good
Daniel Murfet
Susan Wei
Biwei Huang
Hui Li
Jesse Gell-Redman
T. Quella
UQCV
24
26
0
22 Oct 2020
Transferable Graph Optimizers for ML Compilers
Yanqi Zhou
Sudip Roy
AmirAli Abdolrashidi
Daniel Wong
Peter C. Ma
...
Mangpo Phitchaya Phothilimtha
Shen Wang
Anna Goldie
Azalia Mirhoseini
James Laudon
GNN
8
53
0
21 Oct 2020
Learning Curves for Analysis of Deep Networks
Derek Hoiem
Tanmay Gupta
Zhizhong Li
Michal Shlapentokh-Rothman
18
24
0
21 Oct 2020
Small Data, Big Decisions: Model Selection in the Small-Data Regime
J. Bornschein
Francesco Visin
Simon Osindero
21
36
0
26 Sep 2020
Pruning Convolutional Filters using Batch Bridgeout
Najeeb Khan
Ian Stavness
28
3
0
23 Sep 2020
Action-Based Representation Learning for Autonomous Driving
Yi Xiao
Felipe Codevilla
C. Pal
Antonio M. López
22
10
0
21 Aug 2020
Geometric compression of invariant manifolds in neural nets
J. Paccolat
Leonardo Petrini
Mario Geiger
Kevin Tyloo
M. Wyart
MLT
55
34
0
22 Jul 2020
Add a SideNet to your MainNet
Adrien Morisot
14
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14 Jul 2020
The Computational Limits of Deep Learning
Neil C. Thompson
Kristjan Greenewald
Keeheon Lee
Gabriel F. Manso
VLM
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508
0
10 Jul 2020
Is SGD a Bayesian sampler? Well, almost
Chris Mingard
Guillermo Valle Pérez
Joar Skalse
A. Louis
BDL
23
51
0
26 Jun 2020
On the Predictability of Pruning Across Scales
Jonathan S. Rosenfeld
Jonathan Frankle
Michael Carbin
Nir Shavit
25
37
0
18 Jun 2020
To Pretrain or Not to Pretrain: Examining the Benefits of Pretraining on Resource Rich Tasks
Sinong Wang
Madian Khabsa
Hao Ma
18
26
0
15 Jun 2020
Language Models are Few-Shot Learners
Tom B. Brown
Benjamin Mann
Nick Ryder
Melanie Subbiah
Jared Kaplan
...
Christopher Berner
Sam McCandlish
Alec Radford
Ilya Sutskever
Dario Amodei
BDL
77
40,200
0
28 May 2020
How fine can fine-tuning be? Learning efficient language models
Evani Radiya-Dixit
Xin Wang
16
63
0
24 Apr 2020
Embedded Large-Scale Handwritten Chinese Character Recognition
Youssouf Chherawala
Hans J. G. A. Dolfing
Ryan S. Dixon
J. Bellegarda
11
5
0
13 Apr 2020
Leveraging GANs to Improve Continuous Path Keyboard Input Models
Akash Mehra
J. Bellegarda
Ojas Bapat
Partha Lal
Xin Wang
8
8
0
06 Apr 2020
SuperMix: Supervising the Mixing Data Augmentation
Ali Dabouei
Sobhan Soleymani
Fariborz Taherkhani
Nasser M. Nasrabadi
19
98
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10 Mar 2020
Slice Tuner: A Selective Data Acquisition Framework for Accurate and Fair Machine Learning Models
Ki Hyun Tae
Steven Euijong Whang
23
39
0
10 Mar 2020
Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks
Blake Bordelon
Abdulkadir Canatar
Cengiz Pehlevan
146
201
0
07 Feb 2020
Scaling Laws for Neural Language Models
Jared Kaplan
Sam McCandlish
T. Henighan
Tom B. Brown
B. Chess
R. Child
Scott Gray
Alec Radford
Jeff Wu
Dario Amodei
264
4,505
0
23 Jan 2020
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
Kihyuk Sohn
David Berthelot
Chun-Liang Li
Zizhao Zhang
Nicholas Carlini
E. D. Cubuk
Alexey Kurakin
Han Zhang
Colin Raffel
AAML
104
3,467
0
21 Jan 2020
Designing for the Long Tail of Machine Learning
Martin Lindvall
J. Molin
HAI
6
2
0
21 Jan 2020
Social and Governance Implications of Improved Data Efficiency
Aaron David Tucker
Markus Anderljung
Allan Dafoe
16
14
0
14 Jan 2020
Value-laden Disciplinary Shifts in Machine Learning
Ravit Dotan
S. Milli
AILaw
27
48
0
03 Dec 2019
Using Error Decay Prediction to Overcome Practical Issues of Deep Active Learning for Named Entity Recognition
Haw-Shiuan Chang
Shankar Vembu
Sunil Mohan
Rheeya Uppaal
Andrew McCallum
4
3
0
17 Nov 2019
An empirical study of the relation between network architecture and complexity
Emir Konuk
Kevin Smith
21
7
0
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Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Colin Raffel
Noam M. Shazeer
Adam Roberts
Katherine Lee
Sharan Narang
Michael Matena
Yanqi Zhou
Wei Li
Peter J. Liu
AIMat
126
19,493
0
23 Oct 2019
Improving Differentially Private Models with Active Learning
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Nicolas Papernot
Sameer Singh
N. Polyzotis
Augustus Odena
SyDa
6
5
0
02 Oct 2019
GDP: Generalized Device Placement for Dataflow Graphs
Yanqi Zhou
Sudip Roy
AmirAli Abdolrashidi
Daniel Wong
Peter C. Ma
...
Ming Zhong
Hanxiao Liu
Anna Goldie
Azalia Mirhoseini
James Laudon
GNN
27
38
0
28 Sep 2019
A Constructive Prediction of the Generalization Error Across Scales
Jonathan S. Rosenfeld
Amir Rosenfeld
Yonatan Belinkov
Nir Shavit
36
205
0
27 Sep 2019
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