The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Online identification and tracking of subspaces from highly incomplete information
Open accessAbstract
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 an online incremental algorithm for the matrix completion problem of imputing missing entries of a low-rank matrix. GROUSE performs exceptionally well in practice both in tracking subspaces and as an online algorithm for matrix completion.
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Citations
Cites
A Singular Value Thresholding Algorithm for Matrix Completion
Cai, J.-F., Candès, E. J., & Shen, Z. (2010) · SIAM Journal on Optimization · doi:10.1137/080738970 · Cited by 5,809
The Geometry of Algorithms with Orthogonality Constraints
Edelman, A., Arias, T. A., & Smith, S. T. (1998) · SIAM Journal on Matrix Analysis and Applications · doi:10.1137/s0895479895290954 · Cited by 2,685
Stochastic Approximation and Recursive Algorithms and Applications
(2003) · Stochastic Modelling and Applied Probability · doi:10.1007/b97441 · Cited by 1,838
Diagnosing network-wide traffic anomalies
Lakhina, A., Crovella, M., & Diot, C. (2004) · Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications · doi:10.1145/1015467.1015492 · Cited by 1,039
Matrix Completion From a Few Entries
Keshavan, R. H., Montanari, A., & Oh, S. (2010) · IEEE Transactions on Information Theory · doi:10.1109/tit.2010.2046205 · Cited by 974
Matrix completion from a few entries
Keshavan, R. H., Oh, S., & Montanari, A. (2009) · 2009 IEEE International Symposium on Information Theory · doi:10.1109/isit.2009.5205567 · Cited by 650
Fast low-rank modifications of the thin singular value decomposition
Brand, M. (2006) · Linear Algebra and its Applications · doi:10.1016/j.laa.2005.07.021 · Cited by 491
Tracking a few extreme singular values and vectors in signal processing
Comon, P., & Golub, G. H. (1990) · Proceedings of the IEEE · doi:10.1109/5.58320 · Cited by 489
Streaming Pattern Discovery in Multiple Time-Series
Papadimitriou, S., Sun, J., & Faloutsos, C. (2018) · doi:10.1184/r1/6609941 · Cited by 348
Local Minima and Convergence in Low-Rank Semidefinite Programming
Burer, S., & Monteiro, R. D. C. (2005) · Mathematical Programming · doi:10.1007/s10107-004-0564-1 · Cited by 347
Cited by
Parallel stochastic gradient algorithms for large-scale matrix completion
Recht, B., & Ré, C. (2013) · Mathematical Programming Computation · doi:10.1007/s12532-013-0053-8 · Cited by 300
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Metadata
- Authors
- Balzano, L., Nowak, R., & Recht, B.
- Venue
- 2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)
- Publisher
- IEEE
- Published
- 2010-09
- Pages
- 704-711
- OpenAlex
- W2151358751
- Cited by
- 331
- References
- 12
- FWCI
- 37.32
- Type
- conference paper
- Language
- en
- Open access
- green
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- Balzano, L., Nowak, R., & Recht, B. (2010). Online identification and tracking of subspaces from highly incomplete information. 2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton). https://doi.org/10.1109/allerton.2010.5706976
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