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FSTTCS
2008
Springer
14 years 11 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»
14 years 10 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»
15 years 10 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
FOCS
2008
IEEE
14 years 10 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 2 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