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Method for performing federated learning in non-convex problems
​ FeCA roadmap. 1st column: The centralized dataset distributed to clients. 2nd column: The k-means clustering results on different clients under non-IID data sample scenario, where black triangles and squares represent centroids. 3rd column: Eliminating one-fit-many centroids in Algorithm 2, indicated by hollow squares and triangles. 4th column: Centroids...
Published: 4/15/2026   |   Updated: 4/14/2026   |   Inventor(s): Yuqian Zhang, Wei-Lun Chao, Jinxuan Xu
Keywords(s):  
Category(s): Technology Classifications > Artificial Intelligence & Machine Learning, Technology Classifications > Software & Algorithms