CHEESE: distributed clustering-based hybrid federated Split learning over edge networks
Implementing either Federated learning (FL) or split learning (SL) over clients with limited
computation/communication resources faces challenges on achieving delay-efficient model …
computation/communication resources faces challenges on achieving delay-efficient model …
Network for Distributed Intelligence: A Survey and Future Perspectives
To keep pace with the explosive growth of Artificial Intelligence (AI) and Machine Learning
(ML)-dominated applications, distributed intelligence solutions are gaining momentum …
(ML)-dominated applications, distributed intelligence solutions are gaining momentum …
FlexSplit: A Configurable, Privacy-Preserving Federated-Split Learning Framework
T Wu, HMND Bandara, PL Yeoh… - 2023 IEEE …, 2023 - ieeexplore.ieee.org
In this paper, we address the challenges of preserving client data and model sharing privacy
in a distributed machine learning system. Different from conventional federated learning …
in a distributed machine learning system. Different from conventional federated learning …
Machine Learning Orchestration in Cloud Environments: Automating the Training and Deployment of Distributed Machine Learning AI Model
I Sakthidevi, GV Rajkumar, R Sunitha… - … Conference on I …, 2023 - ieeexplore.ieee.org
The rapid advancement of machine learning (ML) and artificial intelligence (AI) has created
an increasing demand for efficient and automated processes in training and deploying AI …
an increasing demand for efficient and automated processes in training and deploying AI …