MOSES: A Streaming Algorithm for Linear Dimensionality Reduction

This paper introduces Memory-limited Online Subspace Estimation Scheme (MOSES) for both estimating the principal components of streaming data and reducing its dimension. More specifically, in various applications such as sensor networks, the data vectors are presented sequentially to a user who has...

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Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence Jg. 42; H. 11; S. 2901 - 2911
Hauptverfasser:	Eftekhari, Armin, Hauser, Raphael A., Grammenos, Andreas
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.11.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Approximation algorithms Dimensionality reduction Ear Empirical analysis Estimation linear dimensionality reduction non-convex optimisation Optimization Principal component analysis Statistical analysis streaming algorithms subspace identification
ISSN:	0162-8828, 1939-3539, 2160-9292, 1939-3539
Online-Zugang:	Volltext
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