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» Rank Estimation in Missing Data Matrix Problems
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CVPR
2011
IEEE
13 years 26 days ago
A Closed Form Solution to Robust Subspace Estimation and Clustering
We consider the problem of fitting one or more subspaces to a collection of data points drawn from the subspaces and corrupted by noise/outliers. We pose this problem as a rank m...
Paolo Favaro, René, Vidal, Avinash Ravichandran
RECSYS
2009
ACM
13 years 12 months ago
Collaborative prediction and ranking with non-random missing data
A fundamental aspect of rating-based recommender systems is the observation process, the process by which users choose the items they rate. Nearly all research on collaborative ...
Benjamin M. Marlin, Richard S. Zemel
CORR
2010
Springer
208views Education» more  CORR 2010»
13 years 2 months ago
Real-time Robust Principal Components' Pursuit
In the recent work of Candes et al, the problem of recovering low rank matrix corrupted by i.i.d. sparse outliers is studied and a very elegant solution, principal component pursui...
Chenlu Qiu, Namrata Vaswani
CORR
2010
Springer
111views Education» more  CORR 2010»
13 years 2 months ago
Calibration for Ultrasound Breast Tomography Using Matrix Completion
We study the calibration problem in circular ultrasound tomography devices for breast imaging, where the sensor positions deviate from the circumference of a perfect circle. We in...
Reza Parhizkar, Amin Karbasi, Sewoong Oh, Martin V...
IWPEC
2004
Springer
13 years 10 months ago
Perfect Path Phylogeny Haplotyping with Missing Data Is Fixed-Parameter Tractable
Abstract. Haplotyping via perfect phylogeny is a method for retrieving haplotypes from genotypes. Fast algorithms are known for computing perfect phylogenies from complete and erro...
Jens Gramm, Till Nierhoff, Till Tantau