Machine Learning Model Updates in Edge Computing: An Optimal Stopping Theory Approach-Reference-Cited by-同舟云学术

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Machine Learning Model Updates in Edge Computing: An Optimal Stopping Theory Approach

Published:2019-06 Issue: Volume: Page:
ISSN:
Container-title:2019 18th International Symposium on Parallel and Distributed Computing (ISPDC)
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Author:

Aleksandrova Ekaterina,Anagnostopoulos Christos,Kolomvatsos Kostas

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8782979/8790823/08790846.pdf?arnumber=8790846

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Formal Algebraic Model of an Edge Data Center with a Redundant Ring Topology;Network;2023-01-30

2. Edge Intelligence: Concepts, Architectures, Applications, and Future Directions;ACM Transactions on Embedded Computing Systems;2022-09-30

3. Fingerprinting-based Indoor and Outdoor Localization with LoRa and Deep Learning;GLOBECOM 2020 - 2020 IEEE Global Communications Conference;2020-12

4. Investigation of the Performance of TDoA-Based Localization Over LoRaWAN in Theory and Practice;Sensors;2020-09-23

5. Yeast and bacterial inoculation practices influence the microbial communities of barrel‐fermented Chardonnay wines;Australian Journal of Grape and Wine Research;2020-06-14

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