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84
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FSTTCS
2008
Springer
15 years 2 months ago
Dynamic matrix rank with partial lookahead
We consider the problem of maintaining information about the rank of a matrix M under changes to its entries. For an n × n matrix M, we show an amortized upper bound of O(nω−1)...
Telikepalli Kavitha
AUTOMATICA
2006
137views more  AUTOMATICA 2006»
15 years 1 months ago
A Newton-like method for solving rank constrained linear matrix inequalities
This paper presents a Newton-like algorithm for solving systems of rank constrained linear matrix inequalities. Though local quadratic convergence of the algorithm is not a priori...
Robert Orsi, Uwe Helmke, John B. Moore
STOC
2001
ACM
138views Algorithms» more  STOC 2001»
16 years 2 months ago
Fast computation of low rank matrix
Given a matrix A, it is often desirable to find a good approximation to A that has low rank. We introduce a simple technique for accelerating the computation of such approximation...
Dimitris Achlioptas, Frank McSherry
115
Voted
FOCS
2008
IEEE
15 years 2 months ago
Matrix Sparsification for Rank and Determinant Computations via Nested Dissection
The nested dissection method developed by Lipton, Rose, and Tarjan is a seminal method for quickly performing Gaussian elimination of symmetric real positive definite matrices who...
Raphael Yuster
APPROX
2006
Springer
179views Algorithms» more  APPROX 2006»
15 years 5 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