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cs.LG2026
Riemannian Difference-of-Convex Optimization for K-Means Clustering
Meng Xu, Bo Jiang, Hanfu Zhang +2
K-means is a widely adopted clustering approach in signal processing and machine learning. In this paper, we study K-means clustering through a cardinality-constrained formulation…
cs.LG2024
Nonconvex Federated Learning on Compact Smooth Submanifolds With Heterogeneous Data
Jiaojiao Zhang, Jiang Hu, Anthony Man-Cho So +1
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 wor…