Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Xiaoxin Su"'
Publikováno v:
IEEE Transactions on Parallel and Distributed Systems. :1-14
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f00e89bf96611106cfff2b20bf193be5
https://doi.org/10.1109/tpds.2023.3240883
https://doi.org/10.1109/tpds.2023.3240883
Publikováno v:
IEEE Internet of Things Journal. 9:14151-14161
Edge computing architectures can help us quickly process the data collected by Internet of Things (IoT) and caching files to edge nodes can speed up the response speed of IoT devices requesting files. Blockchain architectures can help us ensure the s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cac04008317afcca013d822833cab7b4
https://doi.org/10.1109/jiot.2020.3014370
https://doi.org/10.1109/jiot.2020.3014370
Recently, blockchain-based federated learning (BFL) has attracted intensive research attention due to that the training process is auditable and the architecture is serverless avoiding the single point failure of the parameter server in vanilla feder
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::605c40b2d7dc094f6694c6236d072f45
http://arxiv.org/abs/2208.06095
http://arxiv.org/abs/2208.06095
Publikováno v:
IEEE INFOCOM 2022 - IEEE Conference on Computer Communications.
Federated Learning (FL) incurs high communication overhead, which can be greatly alleviated by compression for model updates. Yet the tradeoff between compression and model accuracy in the networked environment remains unclear and, for simplicity, mo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a00ccb7997f2f9cc4a6f1b5ad6fa00b0
https://doi.org/10.1109/infocom48880.2022.9796982
https://doi.org/10.1109/infocom48880.2022.9796982
Federated Learning (FL) is an emerging decentralized learning framework through which multiple clients can collaboratively train a learning model. However, a major obstacle that impedes the wide deployment of FL lies in massive communication traffic.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f7203301cd4730dff73051faa3460b8f
http://arxiv.org/abs/2105.04153
http://arxiv.org/abs/2105.04153
Publikováno v:
GLOBECOM
Recently, Federated Learning (FL) has drawn tremendous attentions due to its ability to protect client’s privacy. In FL, clients collaboratively train machine learning models by merely sharing intermediate computations, i.e., gradients of model par
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bcd201c3fc0de1f926e8379a8238511e
https://doi.org/10.1109/globecom42002.2020.9322527
https://doi.org/10.1109/globecom42002.2020.9322527
Publikováno v:
UMAP Journal; Fall2020, Vol. 41 Issue 3, p301-320, 20p
Autor:
Wei Huang, Xiaoxin Su
Publikováno v:
International Journal of Navigation and Observation.
This paper deals with the design of a fault detection and isolation (FDI) system for an intelligent vehicle, a vehicle equipped with advanced driver assistance system (ADAS). The ADASs are outfitted with sensors for acquiring various information abou
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c404b2d0f8b624cccd7a6122c3e7fc8e
Publikováno v:
Applied Methods and Techniques for Mechatronic Systems ISBN: 9783642363849
The development of Advanced Driver Assistance System (ADAS) is emphasized in road transportation research. Reliability and safety is one of the most important issues in the design process of ADAS. In general, the system must fuse information from mul
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::76504137a21cf8de65bf17f51be4e360
https://doi.org/10.1007/978-3-642-36385-6_20
https://doi.org/10.1007/978-3-642-36385-6_20
Autor:
Shen, Meng1 (AUTHOR) shenmeng@bit.edu.cn, Tan, Zhehui1 (AUTHOR) zhehuitan@bit.edu.cn, Niyato, Dusit2 (AUTHOR) niyato@ntu.edu.sg, Liu, Yuzhi1 (AUTHOR) liuyuzhi@bit.edu.cn, Kang, Jiawen3 (AUTHOR) kavinkang@gdut.edu.cn, Xiong, Zehui4 (AUTHOR) zehui_xiong@sutd.edu.sg, Zhu, Liehuang1 (AUTHOR) liehuangz@bit.edu.cn, Wang, Wei5 (AUTHOR) wangwei1@bjtu.edu.cn, Shen, Xuemin6 (AUTHOR) sshen@uwaterloo.ca
Publikováno v:
ACM Computing Surveys. Oct2024, Vol. 56 Issue 10, p1-39. 39p.