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Alloy: A Fusing Algorithm for Adaptive Video Streaming with Meta-Reinforcement Learning

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dc.contributor.authorChoi ,Wangyu-
dc.contributor.authorYoon, Jong won-
dc.date.accessioned2023-09-04T05:37:34Z-
dc.date.available2023-09-04T05:37:34Z-
dc.date.issued2022-09-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/114704-
dc.description.abstractIn this work, we propose Alloy, an ABR algorithm that fuses existing algorithms to cover a wide variety of environments. Alloy provides high QoE to all users by combining the strengths of various algorithms. To do this, we find transferable parameters between multiple algorithms via meta-updates. Finally, with transferable parameters, Alloy covers a wide range of environments, providing different policies in different environments with just a few update steps.-
dc.format.extent2-
dc.language영어-
dc.language.isoENG-
dc.publisherKICS-
dc.titleAlloy: A Fusing Algorithm for Adaptive Video Streaming with Meta-Reinforcement Learning-
dc.typeArticle-
dc.publisher.location대한민국-
dc.identifier.bibliographicCitation3rd Korea Artificial Intelligence Conference, pp 216 - 217-
dc.citation.title3rd Korea Artificial Intelligence Conference-
dc.citation.startPage216-
dc.citation.endPage217-
dc.type.docTypeProceeding-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassother-
dc.identifier.urlhttps://journal-home.s3.ap-northeast-2.amazonaws.com/site/koreaai2022/abs/0166F.pdf-
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ERICA 소프트웨어융합대학 (ERICA 컴퓨터학부)
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