Efficient Computation of Robust Weighted Low-Rank Matrix Approximations Using the L_1 Norm

IEEE Transactions on Pattern Analysis and Machine Intelligence ◽

10.1109/tpami.2012.116 ◽

2012 ◽

Vol 34 (9) ◽

pp. 1681-1690 ◽

Author(s):

A. Eriksson ◽

A. van den Hengel

Keyword(s):

Low Rank ◽

Efficient Computation ◽

Rank Matrix ◽

Low Rank Matrix ◽

Matrix Approximations

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Efficient computation of robust low-rank matrix approximations in the presence of missing data using the L1 norm

2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition ◽

10.1109/cvpr.2010.5540139 ◽

2010 ◽

Author(s):

Anders Eriksson ◽

Anton van den Hengel

Keyword(s):

Missing Data ◽

Low Rank ◽

Efficient Computation ◽

Rank Matrix ◽

Low Rank Matrix ◽

Matrix Approximations

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Computing optimal low-rank matrix approximations for image processing

2013 Asilomar Conference on Signals, Systems and Computers ◽

10.1109/acssc.2013.6810366 ◽

2013 ◽

Author(s):

Julianne Chung ◽

Matthias Chung

Keyword(s):

Image Processing ◽

Low Rank ◽

Rank Matrix ◽

Low Rank Matrix ◽

Matrix Approximations

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Fast dynamic time warping using low-rank matrix approximations

2015 IEEE Workshop on Signal Processing Systems (SiPS) ◽

10.1109/sips.2015.7344993 ◽

2015 ◽

Author(s):

Mrugesh Gajjar ◽

Naga Vydyanathan

Keyword(s):

Dynamic Time Warping ◽

Low Rank ◽

Time Warping ◽

Rank Matrix ◽

Dynamic Time ◽

Low Rank Matrix ◽

Fast Dynamic ◽

Matrix Approximations

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Subspace-Orbit Randomized Decomposition for Low-Rank Matrix Approximations

IEEE Transactions on Signal Processing ◽

10.1109/tsp.2018.2853137 ◽

2018 ◽

Vol 66 (16) ◽

pp. 4409-4424 ◽

Author(s):

Maboud Farzaneh Kaloorazi ◽

Rodrigo C. de Lamare

Keyword(s):

Low Rank ◽

Rank Matrix ◽

Low Rank Matrix ◽

Matrix Approximations

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Low-Rank Matrix Approximations Do Not Need a Singular Value Gap

SIAM Journal on Matrix Analysis and Applications ◽

10.1137/18m1163658 ◽

2019 ◽

Vol 40 (1) ◽

pp. 299-319 ◽

Author(s):

Petros Drineas ◽

Ilse C. F. Ipsen

Keyword(s):

Singular Value ◽

Low Rank ◽

Rank Matrix ◽

Low Rank Matrix ◽

Matrix Approximations

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Low-rank matrix approximations for Coherent point drift

Pattern Recognition Letters ◽

10.1016/j.patrec.2014.10.005 ◽

2015 ◽

Vol 52 ◽

pp. 53-58 ◽

Author(s):

Ján Dupej ◽

Václav Krajíček ◽

Josef Pelikán

Keyword(s):

Low Rank ◽

Rank Matrix ◽

Coherent Point Drift ◽

Low Rank Matrix ◽

Matrix Approximations

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On Low Rank Matrix Approximations with Applications to Synthesis Problem in Compressed Sensing

SIAM Journal on Matrix Analysis and Applications ◽

10.1137/100792251 ◽

2011 ◽

Vol 32 (3) ◽

pp. 1019-1029 ◽

Author(s):

Anatoli Juditsky ◽

Fatma Kilinç karzan ◽

Arkadi Nemirovski

Keyword(s):

Compressed Sensing ◽

Synthesis Problem ◽

Low Rank ◽

Rank Matrix ◽

Low Rank Matrix ◽

Matrix Approximations

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Fast Parallel Randomized QR with Column Pivoting Algorithms for Reliable Low-Rank Matrix Approximations

2017 IEEE 24th International Conference on High Performance Computing (HiPC) ◽

10.1109/hipc.2017.00035 ◽

2017 ◽

Author(s):

Jianwei Xiao ◽

Ming Gu ◽

Julien Langou

Keyword(s):

Low Rank ◽

Rank Matrix ◽

Column Pivoting ◽

Low Rank Matrix ◽

Matrix Approximations

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Fast computation of Gaussian likelihoods using low-rank matrix approximations

2011 IEEE Workshop on Signal Processing Systems (SiPS) ◽

10.1109/sips.2011.6088983 ◽

2011 ◽

Author(s):

Mrugesh R. Gajjar ◽

T. V. Sreenivas ◽

R. Govindarajan

Keyword(s):

Low Rank ◽

Fast Computation ◽

Rank Matrix ◽

Low Rank Matrix ◽

Matrix Approximations

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Fast computation of low rank matrix approximations

Proceedings of the thirty-third annual ACM symposium on Theory of computing - STOC '01 ◽

10.1145/380752.380858 ◽

2001 ◽

Author(s):

Dimitris Achlioptas ◽

Frank McSherry

Keyword(s):

Low Rank ◽

Fast Computation ◽

Rank Matrix ◽

Low Rank Matrix ◽

Matrix Approximations

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