• DOI:10.1109/ALLERTON.2010.5706976
Corpus ID: 8362137

Online identification and tracking of subspaces from highly incomplete information

@article{Balzano2010OnlineIA,
  title={Online identification and tracking of subspaces from highly incomplete information},
  author={Laura Balzano and R. Nowak and B. Recht},
  journal={2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)},
  year={2010},
  pages={704-711}
}

Laura Balzano, R. Nowak, B. Recht

Published 2010

Computer Science, Mathematics

2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)

This work presents GROUSE (Grassmanian Rank-One Update Subspace Estimation), an efficient online algorithm for tracking subspaces from highly incomplete observations. GROUSE requires only basic linear algebraic manipulations at each iteration, and each subspace update can be performed in linear time in the dimension of the subspace. The algorithm is derived by analyzing incremental gradient descent on the Grassmannian manifold of subspaces. With a slight modification, GROUSE can also be used as… CONTINUE READING

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