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FOCS
1998
IEEE
15 years 2 months ago
Fast Monte-Carlo Algorithms for Finding Low-Rank Approximations
Alan M. Frieze, Ravi Kannan, Santosh Vempala
PCI
2001
Springer
15 years 2 months ago
An Experimental Evaluation of a Monte-Carlo Algorithm for Singular Value Decomposition
We demonstrate that an algorithm proposed by Drineas et. al. in [7] to approximate the singular vectors/values of a matrix A, is not only of theoretical interest but also a fast, v...
Petros Drineas, Eleni Drinea, Patrick S. Huggins
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
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
JCC
2006
110views more  JCC 2006»
14 years 10 months ago
Using internal and collective variables in Monte Carlo simulations of nucleic acid structures: Chain breakage/closure algorithm
: This article describes a method for solving the geometric closure problem for simplified models of nucleic acid structures by using the constant bond lengths approximation. The r...
Heinz Sklenar, Daniel Wüstner, Remo Rohs