Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Zheqi, Zhu"'
Publikováno v:
Entropy, Vol 25, Iss 8, p 1205 (2023)
As a promising distributed learning paradigm, federated learning (FL) faces the challenge of communication–computation bottlenecks in practical deployments. In this work, we mainly focus on the pruning, quantization, and coding of FL. By adopting a
Externí odkaz:
https://doaj.org/article/901eb90a0d8b44bdbb8943b10c97910d
Publikováno v:
Entropy, Vol 22, Iss 5, p 591 (2020)
This paper mainly focuses on the problem of lossy compression storage based on the data value that represents the subjective assessment of users when the storage size is still not enough after the conventional lossless data compression. To this end,
Externí odkaz:
https://doaj.org/article/451421d9c38240debf055a5645ebf470
Publikováno v:
IEEE Communications Letters. 25:798-801
In this letter, we propose soft compression, an lossless compression approach to shape coding for images using location index and codebook of designed shapes with various sizes. This method is different from traditional image compression methods, as
Publikováno v:
2022 IEEE Wireless Communications and Networking Conference (WCNC).
Publikováno v:
2021 11th International Conference on Intelligent Control and Information Processing (ICICIP).
Publikováno v:
2021 IEEE International Mediterranean Conference on Communications and Networking (MeditCom).
Publikováno v:
ICC Workshops
Mobile edge computing (MEC) has been widely studied to provide new schemes for communication-computing systems such as industrial Internet of Things (IoTs), vehicular networks, smart city applications, etc. In this work, we mainly investigate on the
As an emerging technique, mobile edge computing (MEC) introduces a new processing scheme for various distributed communication-computing systems such as industrial Internet of Things (IoT), vehicular communication, smart city, etc. In this work, we m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d26e525f256e6c05b18e43e260305b59
http://arxiv.org/abs/2012.14137
http://arxiv.org/abs/2012.14137
Publikováno v:
Entropy
Volume 22
Issue 5
Entropy, Vol 22, Iss 591, p 591 (2020)
Volume 22
Issue 5
Entropy, Vol 22, Iss 591, p 591 (2020)
This paper mainly focuses on the problem of lossy compression storage based on the data value that represents the subjective assessment of users when the storage size is still not enough after the conventional lossless data compression. To this end,
There are numerous scenarios in source coding where not only the code length but the importance of each value should also be taken into account. Different from the traditional coding theorems, by adding the importance weights for the length of the co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b131d85743e407a71826e5670a90da67
http://arxiv.org/abs/2005.10718
http://arxiv.org/abs/2005.10718