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- W2950958640 abstract "This paper considers the problem of robust subspace recovery: given a set of $N$ points in $mathbb{R}^D$, if many lie in a $d$-dimensional subspace, then can we recover the underlying subspace? We show that Tyler's M-estimator can be used to recover the underlying subspace, if the percentage of the inliers is larger than $d/D$ and the data points lie in general position. Empirically, Tyler's M-estimator compares favorably with other convex subspace recovery algorithms in both simulations and experiments on real data sets." @default.
- W2950958640 created "2019-06-27" @default.
- W2950958640 creator A5033785543 @default.
- W2950958640 date "2012-06-06" @default.
- W2950958640 modified "2023-09-23" @default.
- W2950958640 title "Robust subspace recovery by Tyler's M-estimator" @default.
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- W2950958640 doi "https://doi.org/10.48550/arxiv.1206.1386" @default.
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