Efficient Federated Low Rank Matrix Recovery via Alternating GD and Minimization: A Simple Proof

This note provides a significantly simpler and shorter proof of our sample complexity guarantee for solving the low rank column-wise sensing problem using the Alternating Gradient Descent (GD) and Minimization (AltGDmin) algorithm. AltGDmin was developed and analyzed for solving this problem in our...

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Bibliographic Details
Published in:IEEE transactions on information theory Vol. 70; no. 7; pp. 5162 - 5167
Main Author: Vaswani, Namrata
Format: Journal Article
Language:English
Published: New York IEEE 01.07.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Complexity theory
federated learning
Low rank column-wise sensing (LRCS)
Minimization
multi-task representation learning
Optimization
Partitioning algorithms
Sensors
Time complexity
Vectors
ISSN:0018-9448, 1557-9654
Online Access:Get full text
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Summary:This note provides a significantly simpler and shorter proof of our sample complexity guarantee for solving the low rank column-wise sensing problem using the Alternating Gradient Descent (GD) and Minimization (AltGDmin) algorithm. AltGDmin was developed and analyzed for solving this problem in our recent work. We also provide an improved guarantee.
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ISSN:0018-9448
1557-9654
DOI:10.1109/TIT.2024.3365795