Degree Type

Creative Component

Semester of Graduation

Summer 2019

Department

Electrical and Computer Engineering

First Major Professor

Namrata Vaswani

Degree(s)

Master of Science (MS)

Major(s)

Electrical Engineering

Abstract

We study the problem of subspace tracking (ST) in the presence of missing and corrupted data. We are able to show that, under assumptions on only the algorithm inputs (input data and/or initialization), the output subspace estimates are close to the true data subspaces at all times. The guarantees hold under mild and easily interpretable assumptions and handle time-varying subspaces. We also show that our algorithm and its extensions are fast and have competitive experimental performance when compared with existing methods. Finally, this solution can be interpreted as a provably correct mini-batch and memory-efficient solution to low rank Matrix Completion (MC).

Copyright Owner

Daneshpajooh, Vahid

File Format

PDF

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