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Found 5 papers, 1 papers with code
Federated Unlearning: A Survey on Methods, Design Guidelines, and Evaluation Metrics
This highlights the necessity for novel Federated Unlearning (FU) algorithms, which can efficiently remove specific clients' contributions without full model retraining.
Knowledge Distillation for Federated Learning: a Practical Guide
Federated Learning (FL) enables the training of Deep Learning models without centrally collecting possibly sensitive raw data.
AI and 6G into the Metaverse: Fundamentals, Challenges and Future Research Trends
It is anticipated that Metaverse will be a continuum of rapidly emerging technologies, usecases, capabilities, and experiences that will make it up for the next evolution of the Internet.
IIFNet: A Fusion based Intelligent Service for Noisy Preamble Detection in 6G
We propose an informative instance-based fusion network (IIFNet) to cope with random noise and to improve detection performance, simultaneously.
Towards Energy Efficient Distributed Federated Learning for 6G Networks
The provision of communication services via portable and mobile devices, such as aerial base stations, is a crucial concept to be realized in 5G/6G networks.
