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We develop the first stochastic incremental method for calculating the Moore-Penrose pseudoinverse of a real matrix.
Abstract for “On the reciprocal of the general algebraic matrix”
E. H. Moore · 1920
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A generalized inverse for matrices
R. Penrose · 1955
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A note on pseudoinverses
C. A. Desoer and B. H. Whalen · 1963
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An iterative method for computing the generalized inverse of a matrix
Adi Ben-Israel · 1965
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On iterative computation of generalized inverses and associated projections
Adi Ben-Israel and Dan Cohen · 1966
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Quasi-Newton methods and their application to function minimisation
C. G. Broyden · 1967
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Inexact Newton methods
Ron S. Dembo, Stanley C. Eisenstat, and Trond Steihaug · 1982
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Projected gradient methods for linearly constrained problems
Paul H. Calamai and Jorge J. Moré · 1987
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Pseudoinverse matrix methods for signal reconstruction from partial data
Hans G. Feichtinger · 1991
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An improved newton iteration for the generalized inverse of a matrix, with applications
Victor Pan and Robert Schreiber · 1991
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Parallel preconditioning with sparse approximate inverses
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The University of Florida sparse matrix collection
Timothy A. Davis and Yifan Hu · 2011
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Convergence analysis of an inexact feasible interior point method for convex quadratic programming
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Learning the pseudoinverse solution to network weights
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Stochastic dual ascent for solving linear systems
Robert M. Gower and Peter Richtárik · 2015
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Randomized iterative methods for linear systems
Robert Mansel Gower and Peter Richtárik · 2015
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Sketch and Project: Randomized Iterative Methods for Linear Systems and Inverting Matrices
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