CONTINUAL NEURAL NETWORK TRAINING IN AN EDGE COMPUTING ENVIRONMENT

Abstract: continual neural network training in an edge computing environment includes deploying a plurality of copies of a centralized neural network respectively to a corresponding plurality of edge servers, wherein each of the copies of the centralized neural network is independently operated and trained at a respective one of the edge servers based on inputs received at that edge server to create independently trained neural networks. at periodic intervals, copies of the independently trained neural networks and a corresponding fitness measure for each of the copies of the independently trained neural networks are sent from the plurality of edge servers to a cloud-based data center. the centralized neural network is updated at the cloud-based data center, including performing neural network breeding based on the copies of the independently trained neural networks sent from the plurality of edge servers.

Inventor(s): ANDREW C. M. HICKS, JOHN S. WERNER, RAFAELA FROTA, FAEZEH GHOLAMI

CPC Classification: G06N3/096 (Transfer learning)

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