Measurement-based Admission Control in Sliced Networks: A Best Arm Identification Approach-Reference-Cited by-同舟云学术

Measurement-based Admission Control in Sliced Networks: A Best Arm Identification Approach

Published:2022-12-04 Issue: Volume: Page:
ISSN:
Container-title:GLOBECOM 2022 - 2022 IEEE Global Communications Conference
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Author:

Lindstahl Simon¹,Proutiere Alexandre¹,Johnsson Andreas²

Affiliation:

1. KTH Royal Institute of Technology,EECS and Digital futures,Sweden

2. Ericsson Research,Sweden

Funder

Knut and Alice Wallenberg Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10000063/10000593/10001053.pdf?arnumber=10001053

Reference22 articles.

1. Optimal best arm identification with fixed confidence;garivier;Conference on Learning Theory,2016

2. Action elimination and stopping conditions for the multi -armed bandit and reinforcement learning problems;even-dar;Journal of Machine Learning Research,2006

3. Thresholding bandit for dose-ranging: The impact of monotonicity;garivier;Proceedings of International Conference on Machine Learning Artificial Intelligence and Applications,2020

4. Pure exploration with multiple correct answers;degenne;Proceedings of the 33rd International Conference on Neural Information Processing Systems,2019

5. Measurement-based admission control in sliced networks: A best arm identification approach;lindståhl;ArXiv Preprint,2022

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3. Automatic Network Slicing for Underwater Acoustic Communication Systems Admission Control, Routing, and Resource Allocation;2023 International Conference on Data Science and Network Security (ICDSNS);2023-07-28