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• W2947168387 abstract "We study the problem of subspace tracking in the presence of missing data (ST-miss). In recent work, we studied a related problem called robust ST. In this work, we show that a simple modification of our robust ST solution also provably solves ST-miss and robust ST-miss. To our knowledge, our result is the first `complete' guarantee for ST-miss. This means that we can prove that under assumptions on only the algorithm inputs, the output subspace estimates are close to the true data subspaces at all times. Our guarantees hold under mild and easily interpretable assumptions, and allow the underlying subspace to change with time in a piecewise constant fashion. In contrast, all existing guarantees for ST are partial results and assume a fixed unknown subspace. Extensive numerical experiments are shown to back up our theoretical claims. Finally, our solution can be interpreted as a provably correct mini-batch and memory-efficient solution to low-rank Matrix Completion (MC)." @default.
• W2947168387 created "2019-06-07" @default.
• W2947168387 creator A5005043504 @default.
• W2947168387 creator A5023728903 @default.
• W2947168387 creator A5087330283 @default.
• W2947168387 date "2018-10-06" @default.
• W2947168387 modified "2023-09-27" @default.
• W2947168387 title "Subspace Tracking from Missing and Outlier Corrupted Data." @default.
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• W2947168387 hasPublicationYear "2018" @default.
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