FL-HDC: Hyperdimensional Computing Design for the Application of Federated Learning

Federated learning (FL) is a privacy-preserving learning framework, which collaboratively learns a centralized model across edge devices. Each device trains an independent model with its local dataset and only uploads model parameters to mitigate privacy concerns. However, most FL works focus on deep neural networks (DNNs), whose intensive computation hinders FL from practical realization on resou...