Zobrazeno 1 - 10
of 383
pro vyhledávání: '"personalized federated learning"'
Publikováno v:
In Neurocomputing 7 February 2025 617
Publikováno v:
Complex & Intelligent Systems, Vol 10, Iss 3, Pp 3577-3592 (2024)
Abstract As a new distributed machine learning paradigm, federated learning has gained increasing attention in the industry and research community. However, federated learning is challenging to implement on edge devices with limited resources and het
Externí odkaz:
https://doaj.org/article/d257993d550f4eb192d7d30f873e0a51
Publikováno v:
Applied Sciences, Vol 14, Iss 22, p 10236 (2024)
The rise of Distributed Denial of Service (DDoS) attacks on the internet has necessitated the development of robust and efficient detection mechanisms. DDoS attacks continue to present a significant threat, making it imperative to find efficient ways
Externí odkaz:
https://doaj.org/article/a73df1c1265540c59a490c2c5b21e8c2
Publikováno v:
IEEE Access, Vol 12, Pp 148026-148036 (2024)
Existing short-term traffic flow prediction methods are based on centralized learning frameworks, which do not consider the diversity of data, leading to limited predictive performance. Additionally, these methods face challenges related to computati
Externí odkaz:
https://doaj.org/article/a35d54c21eee4cc8ac685fd11ceacb85
Publikováno v:
CSEE Journal of Power and Energy Systems, Vol 10, Iss 5, Pp 2265-2270 (2024)
A centralized framework-based data-driven framework for active distribution system state estimation (DSSE) has been widely leveraged. However, it is challenged by potential data privacy breaches due to the aggregation of raw measurement data in a dat
Externí odkaz:
https://doaj.org/article/f4b7978da09c4d36afa10fa2fb7cd443
Publikováno v:
IEEE Access, Vol 12, Pp 53126-53140 (2024)
With the evolution of mobile networks delivering high-performance network services to a myriad of devices, accurate mobile traffic prediction has become increasingly important. In recent years, federated learning (FL) has emerged as a communication-e
Externí odkaz:
https://doaj.org/article/c3735d89ed0e4af59071fd69929aeeea
Publikováno v:
IEEE Open Journal of the Communications Society, Vol 5, Pp 1325-1339 (2024)
Malicious traffic has posed a significant threat to current 5G networks. In the upcoming 6G era, with the rapid development of the Internet of Things (IoT), defending against malicious traffic has become even more challenging due to the diverse natur
Externí odkaz:
https://doaj.org/article/243a119a87f64255b605dc1e5459758b
Publikováno v:
IEEE Access, Vol 12, Pp 10135-10145 (2024)
In the era of a more advanced and intelligent Internet, the highly sophisticated service-oriented internet provides users with a diverse array of similar services. Accurate Quality of Service (QoS) prediction plays a pivotal role in helping users cho
Externí odkaz:
https://doaj.org/article/1c70dea2b7664041b31c775f418d572b
Publikováno v:
Big Data Mining and Analytics, Vol 6, Iss 4, Pp 421-432 (2023)
Accurate load forecasting is critical for electricity production, transmission, and maintenance. Deep learning (DL) model has replaced other classical models as the most popular prediction models. However, the deep prediction model requires users to
Externí odkaz:
https://doaj.org/article/e96d12cc43804385bff4752aa540d08a
Publikováno v:
Entropy, Vol 26, Iss 9, p 762 (2024)
Federated learning enables multiple devices to collaboratively train a high-performance model on the central server while keeping their data on the devices themselves. However, due to the significant variability in data distribution across devices, t
Externí odkaz:
https://doaj.org/article/1eab5d52ce0d4b9e9f3be4a61f1c0c70