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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 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
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