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» Generalized low rank approximations of matrices
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SIAMJO
2011
13 years 1 months ago
Recovering Low-Rank and Sparse Components of Matrices from Incomplete and Noisy Observations
Many applications arising in a variety of fields can be well illustrated by the task of recovering the low-rank and sparse components of a given matrix. Recently, it is discovered...
Min Tao, Xiaoming Yuan
APPROX
2006
Springer
179views Algorithms» more  APPROX 2006»
13 years 10 months ago
Adaptive Sampling and Fast Low-Rank Matrix Approximation
We prove that any real matrix A contains a subset of at most 4k/ + 2k log(k + 1) rows whose span "contains" a matrix of rank at most k with error only (1 + ) times the er...
Amit Deshpande, Santosh Vempala
MOR
2008
109views more  MOR 2008»
13 years 6 months ago
A Unified Theorem on SDP Rank Reduction
We consider the problem of finding a low
Anthony Man-Cho So, Yinyu Ye, Jiawei Zhang
COLT
2005
Springer
13 years 11 months ago
Rank, Trace-Norm and Max-Norm
We study the rank, trace-norm and max-norm as complexity measures of matrices, focusing on the problem of fitting a matrix with matrices having low complexity. We present generali...
Nathan Srebro, Adi Shraibman
DAGSTUHL
2007
13 years 7 months ago
Multidamping simulation framework for link-based ranking
We outline an approach for re-interpreting methods for ranking web pages based on interesting recent work on matrix power series representations for PageRank and its variants, such...
Giorgios Kollias, Efstratios Gallopoulos