6533b7d7fe1ef96bd12683fd
RESEARCH PRODUCT
Average Performance Analysis of the Stochastic Gradient Method for Online PCA
Stéphane ChrétienZhen-wai Olivier HoChristophe Guyeuxsubject
Computer Science::Machine Learning[STAT.ML]Statistics [stat]/Machine Learning [stat.ML]Computer science0502 economics and business05 social sciencesMathematicsofComputing_NUMERICALANALYSISRelevance (information retrieval)050207 economics010501 environmental sciencesStochastic gradient method01 natural sciencesAlgorithm0105 earth and related environmental sciencesdescription
International audience; This paper studies the complexity of the stochastic gradient algorithm for PCA when the data are observed in a streaming setting. We also propose an online approach for selecting the learning rate. Simulation experiments confirm the practical relevance of the plain stochastic gradient approach and that drastic improvements can be achieved by learning the learning rate.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2019-01-01 |