Publications related to Randomized Extended Kaczmarz For Solving Least Squares

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The standard framework to study vision is typically hierarchical and feedforward, which facilitates deconstructing complex mechanisms into smaller, more tractable problems. However, this framework can fail when elements are presented in context, as they ar ...

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ALS Scheme using Extent-based Constraints for the Analysis of Chemical Reaction Systems

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Low-rank methods for parameter-dependent eigenvalue problems and matrix equations

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The focus of this thesis is on developing efficient algorithms for two important problems arising in model reduction, estimation of the smallest eigenvalue for a parameter-dependent Hermitian matrix and solving large-scale linear matrix equations, by extra ...

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Reduced Basis Methods: From Low-Rank Matrices To Low-Rank Tensors

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A New Identity for the Least-square Solution of Overdetermined Set of Linear Equations

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In this paper, we prove a new identity for the least-square solution of an over-determined set of linear equation

Ax=b

, where

A

is an

m\times n

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b

is a column-vector of dimension

m

, and

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A New Identity for the Least-square Solution of Overdetermined Set of Linear Equations

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In this paper, we prove a new identity for the least-square solution of an over-determined set of linear equation

Ax=b

, where

A

is an

m\times n

full-rank matrix,

b

is a column-vector of dimension

m

, and

m

(the number of equations) is larger tha ...

Idiap2015

Discrete least squares polynomial approximation with random evaluations − application to parametric and stochastic elliptic PDEs

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Motivated by the numerical treatment of parametric and stochastic PDEs, we analyze the least-squares method for polynomial approximation of multivariate functions based on random sampling according to a given probability measure. Recent work has shown that ...

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Robust distributed detection over adaptive diffusion networks

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Diffusion adaptation techniques based on the least-mean-squares criterion have been proposed for distributed detection of a signal in Gaussian-distributed noise, forgoing the need for a fusion center. However, least-mean-squares solutions are generally non ...

IEEE2014

Randomized Extended Kaczmarz For Solving Least Squares

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The effect of overall stimulus configuration on crowding

ALS Scheme using Extent-based Constraints for the Analysis of Chemical Reaction Systems

Low-rank methods for parameter-dependent eigenvalue problems and matrix equations

Reduced Basis Methods: From Low-Rank Matrices To Low-Rank Tensors

A New Identity for the Least-square Solution of Overdetermined Set of Linear Equations

A New Identity for the Least-square Solution of Overdetermined Set of Linear Equations

Discrete least squares polynomial approximation with random evaluations − application to parametric and stochastic elliptic PDEs

The Squares of Montchoisy. Notes for a History of the Open Form in Geneva

MATHICSE Technical Report : Discrete least squares polynomial approximation with random evaluations – application to parametric and stochastic elliptic PDES

Robust distributed detection over adaptive diffusion networks

The effect of overall stimulus configuration on crowding

Low-rank methods for parameter-dependent eigenvalue problems and matrix equations

ALS Scheme using Extent-based Constraints for the Analysis of Chemical Reaction Systems

Reduced Basis Methods: From Low-Rank Matrices To Low-Rank Tensors

A New Identity for the Least-square Solution of Overdetermined Set of Linear Equations

A New Identity for the Least-square Solution of Overdetermined Set of Linear Equations

Discrete least squares polynomial approximation with random evaluations − application to parametric and stochastic elliptic PDEs

The Squares of Montchoisy. Notes for a History of the Open Form in Geneva

MATHICSE Technical Report : Discrete least squares polynomial approximation with random evaluations – application to parametric and stochastic elliptic PDES

Robust distributed detection over adaptive diffusion networks