Deep Reinforcement Learning with Importance Weighted A3C for QoE enhancement in Video Delivery Services-Reference-Cited by-同舟云学术

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Deep Reinforcement Learning with Importance Weighted A3C for QoE enhancement in Video Delivery Services

Published:2023-06 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 24th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)
language:
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Author:

Naresh Mandan¹,Saxena Paresh¹,Gupta Manik¹

Affiliation:

1. Computer Science & Information Systems Birla Institute of Technology and Science Pilani,Hyderabad,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10195195/10195246/10195508.pdf?arnumber=10195508

Reference35 articles.

1. Federal communications commission. 2016. raw data - measuring broadband america,2016

2. Federated learning: Strategies for improving communication efficiency;kone?ný;NIPS Workshop on Private Multi-Party Machine Learning PMPML '16,2016

3. Mahimahi: Accurate record-and-replay for http;netravali;USENIX ATC ’18,2015

4. Follow then Forage Exploration: Improving Asynchronous Advantage Actor Critic

5. Oboe

Cited by 2 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. DRL Empowered On-policy and Off-policy ABR for 5G Mobile Ultra-HD Video Delivery;Mobile Networks and Applications;2024-03-28

2. GRadient sharing A3C for Adaptive Bitrate (GRAAB): A DRL Based Approach for Adaptive Video Streaming;2024 International Conference on Information Networking (ICOIN);2024-01-17

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