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Orchestrating the Development Lifecycle of Machine Learning-Based IoT
  Applications: A Taxonomy and Survey

Orchestrating the Development Lifecycle of Machine Learning-Based IoT Applications: A Taxonomy and Survey

11 October 2019
Bin Qian
Jie Su
Z. Wen
D. N. Jha
Yinhao Li
Yu Guan
Deepak Puthal
Philip James
Renyu Yang
Albert Y. Zomaya
Omer F. Rana
Lizhe Wang
Maciej Koutny
R. Ranjan
ArXivPDFHTML

Papers citing "Orchestrating the Development Lifecycle of Machine Learning-Based IoT Applications: A Taxonomy and Survey"

4 / 4 papers shown
Title
Efficient Multi-objective Neural Architecture Search via Lamarckian
  Evolution
Efficient Multi-objective Neural Architecture Search via Lamarckian Evolution
T. Elsken
J. H. Metzen
Frank Hutter
131
498
0
24 Apr 2018
Emergence of Locomotion Behaviours in Rich Environments
Emergence of Locomotion Behaviours in Rich Environments
N. Heess
TB Dhruva
S. Sriram
Jay Lemmon
J. Merel
...
Tom Erez
Ziyun Wang
S. M. Ali Eslami
Martin Riedmiller
David Silver
131
928
0
07 Jul 2017
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
261
3,109
0
04 Nov 2016
Effective Approaches to Attention-based Neural Machine Translation
Effective Approaches to Attention-based Neural Machine Translation
Thang Luong
Hieu H. Pham
Christopher D. Manning
218
7,926
0
17 Aug 2015
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