首页|'Zone Gradient Diffusion (Zgd) For Zone-Based Federated Learning' in Patent Appl ication Approval Process (USPTO 20240135192)
'Zone Gradient Diffusion (Zgd) For Zone-Based Federated Learning' in Patent Appl ication Approval Process (USPTO 20240135192)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News - A patent application by the inventors CHEN, An (San Diego, CA, US); MAYYURI, Vijaya Datta (San Diego, CA, US), filed o n September 4, 2023, was made available online on April 25, 2024, according to n ews reporting originating from Washington, D.C., by NewsRx correspondents. This patent application has not been assigned to a company or institution. The following quote was obtained by the news editors from the background informa tion supplied by the inventors: “Federated learning is a machine learning techni que that trains a federated learning model across multiple decentralized edge de vices or servers holding local data samples, without sharing the data samples wi th a central server. Federated learning provides benefits of privacy preserving machine learning and continuous learning on the edge. However, the performance o f federated learning suffers when the data at the devices is non-independent and identically distributed (non-IID). Data augmentation is one approach to address the non-IID data. Another approach is zone-based federated learning.
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