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Found 4 papers, 1 papers with code
Edge Unlearning is Not "on Edge"! An Adaptive Exact Unlearning System on Resource-Constrained Devices
Another approach, exact unlearning, tackles this issue by discarding the data and retraining the model from scratch, but at the cost of considerable computational and memory resources.
Towards Integrated Fine-tuning and Inference when Generative AI meets Edge Intelligence
The high-performance generative artificial intelligence (GAI) represents the latest evolution of computational intelligence, while the blessing of future 6G networks also makes edge intelligence (EI) full of development potential.
Distributed Machine Learning in D2D-Enabled Heterogeneous Networks: Architectures, Performance, and Open Challenges
The ever-growing concerns regarding data privacy have led to a paradigm shift in machine learning (ML) architectures from centralized to distributed approaches, giving rise to federated learning (FL) and split learning (SL) as the two predominant privacy-preserving ML mechanisms.
Prognostication of chronic disorders of consciousness using brain functional networks and clinical characteristics
Disorders of consciousness are a heterogeneous mixture of different diseases or injuries.
Neurons and Cognition
