Oral
Streaming Principal Component Analysis in Noisy Setting
Teodor Vanislavov Marinov · Poorya Mianjy · Raman Arora

Wed Jul 11th 02:20 -- 02:30 PM @ K11

We study streaming algorithms for principal component analysis (PCA) in noisy settings. We present computationally efficient algorithms with sub-linear regret bounds for PCA in the presence of noise, missing data, and gross outliers.

Author Information

Teodor Vanislavov Marinov (Johns Hopkins University)
Poorya Mianjy (Johns Hopkins University)
Raman Arora (Johns Hopkins University)

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