Stochastic optimization for PCA and PLS

Stochastic optimization for PCA and PLS

We study PCA, PLS, and CCA as stochastic optimization problems, of optimizing a population objective based on a sample. We suggest several stochastic approximation (SA) methods for PCA and PLS, and investigate their empirical performance.

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Bibliographische Detailangaben
Hauptverfasser: Arora, R., Cotter, A., Livescu, K., Srebro, N.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Approximation methods
Eigenvalues and eigenfunctions
Equations
Optimization
Principal component analysis
Runtime
Vectors
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Beschreibung
Zusammenfassung:We study PCA, PLS, and CCA as stochastic optimization problems, of optimizing a population objective based on a sample. We suggest several stochastic approximation (SA) methods for PCA and PLS, and investigate their empirical performance.
DOI:10.1109/Allerton.2012.6483308