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Predicting the Computational Cost of Deep Learning Models
28 November 2018
Daniel Justus
John Brennan
Stephen Bonner
A. Mcgough
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Papers citing
"Predicting the Computational Cost of Deep Learning Models"
11 / 61 papers shown
Robust building footprint extraction from big multi-sensor data using deep competition network
M. Khoshboresh-Masouleh
M. Saradjian
248
10
0
04 Nov 2020
Performance Prediction for Convolutional Neural Networks in Edge Devices
Halima Bouzidi
Hamza Ouarnoughi
Smail Niar
A. A. E. Cadi
121
10
0
21 Oct 2020
Optimising the Performance of Convolutional Neural Networks across Computing Systems using Transfer Learning
Rik Mulder
Valentin Radu
Christophe Dubach
101
2
0
20 Oct 2020
I-SiamIDS: an improved Siam-IDS for handling class imbalance in network-based intrusion detection systems
Punam Bedi
Neha Gupta
Dr Vinita Jindal
96
126
0
23 Sep 2020
Predicting Training Time Without Training
Neural Information Processing Systems (NeurIPS), 2020
Luca Zancato
Alessandro Achille
Avinash Ravichandran
Rahul Bhotika
Stefano Soatto
258
29
0
28 Aug 2020
A Learned Performance Model for Tensor Processing Units
Samuel J. Kaufman
P. Phothilimthana
Yanqi Zhou
Charith Mendis
Sudip Roy
Amit Sabne
Mike Burrows
267
8
0
03 Aug 2020
A Heuristically Self-Organised Linguistic Attribute Deep Learning in Edge Computing For IoT Intelligence
Hongmei He
Zhenhuan Zhu
137
1
0
08 Jun 2020
Scientific Calculator for Designing Trojan Detectors in Neural Networks
P. Bajcsy
N. Schaub
Michael Majurski
140
0
0
05 Jun 2020
Characterizing Deep Learning Training Workloads on Alibaba-PAI
IEEE International Symposium on Workload Characterization (IISWC), 2019
Mengdi Wang
Chen Meng
Guoping Long
Chuan Wu
Jun Yang
Jialin Li
Yangqing Jia
146
62
0
14 Oct 2019
Best Practices for Scientific Research on Neural Architecture Search
Marius Lindauer
Katharina Eggensperger
238
152
0
05 Sep 2019
A Survey of the Recent Architectures of Deep Convolutional Neural Networks
Asifullah Khan
A. Sohail
Umme Zahoora
Aqsa Saeed Qureshi
OOD
718
2,540
0
17 Jan 2019
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