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Nonconvex Federated Learning on Compact Smooth Submanifolds With Heterogeneous Data
Many machine learning tasks, such as principal component analysis and low-rank matrix
completion, give rise to manifold optimization problems. Although there is a large body of …
completion, give rise to manifold optimization problems. Although there is a large body of …
Non-convex composite federated learning with heterogeneous data
We propose an innovative algorithm for non-convex composite federated learning that
decouples the proximal operator evaluation and the communication between server and …
decouples the proximal operator evaluation and the communication between server and …
[HTML][HTML] Riemannian SVRG Using Barzilai–Borwein Method as Second-Order Approximation for Federated Learning
H **ao, T Yan, K Wang - Symmetry, 2024 - mdpi.com
In this paper, we propose a modified RFedSVRG method by incorporating the Barzilai–
Borwein (BB) method to approximate second-order information on the manifold for …
Borwein (BB) method to approximate second-order information on the manifold for …