… This motivates us to have a comprehensivesurvey with the following contributions: • We … For each of this challenge, we present to the reader a comprehensive discussion of existing …
… FederatedLearning (FL) has emerged as a distributed … In this article, we provide a comprehensivesurvey of the … We then provide an extensive survey of the use of FL in various key …
DH Mahlool, MH Abed - Mobile Computing and Sustainable Informatics …, 2022 - Springer
… This paper provides a comprehensive study of FederatedLearning (FL) with an emphasis … is critical data, therefore collaborative learning or federatedlearning comes into the picture. …
C Zhang, Y Xie, H Bai, B Yu, W Li, Y Gao - Knowledge-Based Systems, 2021 - Elsevier
… To provide a comprehensivesurvey and facilitate the potential research of this area, we … of federatedlearning from five aspects: data partitioning, privacy mechanism, machine learning …
… But the centralized data in centralized machine learning has limitations such as limited … this comprehensivesurvey on FederatedLearning for smart cities. The FederatedLearning for …
… ABSTRACT This paper provides a comprehensive study of FederatedLearning (FL) with an emphasis on enabling software and hardware platforms, protocols, real-life applications and …
B Liu, N Lv, Y Guo, Y Li - Neurocomputing, 2024 - Elsevier
… the authors provided the definition of federatedlearning systems and analyzed the … surveys only review a specific aspect of federatedlearning, failing to give readers a comprehensive …
Federatedlearning (FL) is a distributed machine learning (ML) approach that enables models to be trained on client devices while ensuring the privacy of user data. Model aggregation, …
R Zeng, C Zeng, X Wang, B Li, X Chu - arXiv preprint arXiv:2106.15406, 2021 - arxiv.org
… In this paper, we present a comprehensivesurvey of incentive schemes for federatelearning. Specifically, we identify the incentive problem in federatedlearning and then provide a …