Search Results - federated+edge+learning

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Methods for Long-Range Federated Edge Learning with Chirp-Based Over-the-Air Computation
Reference #: 01574 The University of South Carolina is offering licensing opportunities for Methods for Long-Range Federated Edge Learning with Chirp-Based Over-the-Air Computation Background: Federated edge learning (FEEL) deploys federated learning (FL) over a wireless network, in which many edge devices (EDs) participate in training using locally...
Published: 1/3/2023   |   Inventor(s): Safi Shams Muhtasimul Hoque, Alphan Sahin
Keywords(s): chirp, DFT-s-OFDM, Distributed learning, federated edge learning, LoRa, orthogonal frequency division multiplexing, over-the-air computation, peak-to-mean envelope power ratio, pulse-position modulation
Category(s): Engineering and Physical Sciences, Software and Computing
Methods for Multi-cell Over-the-Air Computation for Distributed Learning
Reference #: 01573 The University of South Carolina is offering licensing opportunities for Methods for Multi-cell Over-the-Air Computation for Distributed Learning Background: Federated edge learning (FEEL) is a distributed learning framework that leverages the computational powers of edge devices (EDs) and uses the local data at the EDs without...
Published: 5/9/2023   |   Inventor(s): Mohammad Hassan Adeli, Alphan Sahin
Keywords(s): Distributed learning, federated edge learning, frequency-shift keying, orthogonal frequency division multiplexing, over-the-air computation, peak-to-mean envelope power ratio
Category(s): Engineering and Physical Sciences, Software and Computing
Methods for Reliable Over-the-Air Computation with Pulses for Distributed Learning
Reference #: 01541 The University of South Carolina is offering licensing opportunities for Methods for Reliable Over-the-Air Computation with Pulses for Distributed Learning Background: Federated edge learning (FEEL) is an implementation of federated learning (FL) over a wireless network to train a model by using the local data at the edge devices...
Published: 9/3/2022   |   Inventor(s): Alphan Sahin, Everette Bryson, Safi Shams Muhtasimul Hoque
Keywords(s): DFT-s-OFDM, Distributed learning, federated edge learning, orthogonal frequency division multiplexing, over-the-air computation, peak-to-mean envelope power ratio, pulse-position modulation, SC-FDE
Category(s): Software and Computing, Engineering and Physical Sciences
Methods for Reliable Over-the-Air Computation and Federated Edge Learning
Reference #: 01538 The University of South Carolina is offering licensing opportunities for Methods for Reliable Over-the-Air Computation and Federated Edge Learning Background: Federated edge learning (FEEL) is a distributed learning framework that leverages the computational powers of edge devices (EDs) and uses the local data at the EDs without...
Published: 9/3/2022   |   Inventor(s): Alphan Sahin, Everette Bryson, Safi Shams Muhtasimul Hoque
Keywords(s): Distributed learning, federated edge learning, frequency-shift keying, orthogonal frequency division multiplexing, over-the-air computation, peak-to-mean envelope power ratio
Category(s): Engineering and Physical Sciences, Software and Computing