Federated Over-Air Robust Subspace Tracking from Missing Data

IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)(2022)

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摘要
Robust Subspace Tracking with missing data (RST-miss) has been extensively studied in the past decade. In this work we study RST-miss to the setting where the data is federated and when the overair data communication modality is used for information exchange between the K peer nodes and the central server. To the best of our knowledge, there is no existing work in the literature. To this end, we develop the first fast, and provable algorithm that solves RST-miss in a federated over-air setting. We corroborate our theoretical claims with extensive numerical simulations.
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关键词
Robust Subspace Tracking,Robust PCA,Matrix Completion,Federated Learning
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