Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Heterogeneous federated learning: State-of-the-art and research challenges
Federated learning (FL) has drawn increasing attention owing to its potential use in large-
scale industrial applications. Existing FL works mainly focus on model homogeneous …
scale industrial applications. Existing FL works mainly focus on model homogeneous …
Distributed artificial intelligence empowered by end-edge-cloud computing: A survey
As the computing paradigm shifts from cloud computing to end-edge-cloud computing, it
also supports artificial intelligence evolving from a centralized manner to a distributed one …
also supports artificial intelligence evolving from a centralized manner to a distributed one …
Privacy-preserving aggregation in federated learning: A survey
Over the recent years, with the increasing adoption of Federated Learning (FL) algorithms
and growing concerns over personal data privacy, Privacy-Preserving Federated Learning …
and growing concerns over personal data privacy, Privacy-Preserving Federated Learning …
Federated learning for internet of things: Recent advances, taxonomy, and open challenges
The Internet of Things (IoT) will be ripe for the deployment of novel machine learning
algorithm for both network and application management. However, given the presence of …
algorithm for both network and application management. However, given the presence of …
Recent advances on federated learning: A systematic survey
Federated learning has emerged as an effective paradigm to achieve privacy-preserving
collaborative learning among different parties. Compared to traditional centralized learning …
collaborative learning among different parties. Compared to traditional centralized learning …
Fairness and privacy preserving in federated learning: A survey
Federated Learning (FL) is an increasingly popular form of distributed machine learning that
addresses privacy concerns by allowing participants to collaboratively train machine …
addresses privacy concerns by allowing participants to collaboratively train machine …
Exploring homomorphic encryption and differential privacy techniques towards secure federated learning paradigm
The trend of the next generation of the internet has already been scrutinized by top analytics
enterprises. According to Gartner investigations, it is predicted that, by 2024, 75% of the …
enterprises. According to Gartner investigations, it is predicted that, by 2024, 75% of the …
Local differential privacy and its applications: A comprehensive survey
With the rapid development of low-cost consumer electronics and pervasive adoption of next
generation wireless communication technologies, a tremendous amount of data has been …
generation wireless communication technologies, a tremendous amount of data has been …
On privacy and personalization in cross-silo federated learning
While the application of differential privacy (DP) has been well-studied in cross-device
federated learning (FL), there is a lack of work considering DP and its implications for cross …
federated learning (FL), there is a lack of work considering DP and its implications for cross …
The fundamental price of secure aggregation in differentially private federated learning
We consider the problem of training a $ d $ dimensional model with distributed differential
privacy (DP) where secure aggregation (SecAgg) is used to ensure that the server only sees …
privacy (DP) where secure aggregation (SecAgg) is used to ensure that the server only sees …