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Linearly Convergent Randomized Iterative Methods for Computing the Pseudoinverse [PDF]

open access: yes, 2016
28 pages, 10 figuresWe develop the first stochastic incremental method for calculating the Moore-Penrose pseu-doinverse of a real matrix. By leveraging three alternative characterizations of pseudoinverse matrices, we design three methods for calculating
Gower, Robert M., Richtárik, Peter
core   +2 more sources

Recovering Latent Signals from a Mixture of Measurements using a Gaussian Process Prior

open access: yes, 2017
In sensing applications, sensors cannot always measure the latent quantity of interest at the required resolution, sometimes they can only acquire a blurred version of it due the sensor's transfer function. To recover latent signals when only noisy mixed
Guerrero, Pablo   +3 more
core   +1 more source

Lectures on Randomized Numerical Linear Algebra

open access: yes, 2017
This chapter is based on lectures on Randomized Numerical Linear Algebra from the 2016 Park City Mathematics Institute summer school on The Mathematics of Data.Comment: To appear in the edited volume of lectures from the 2016 PCMI summer ...
Drineas, Petros, Mahoney, Michael W.
core   +1 more source

Matrix Pencil Optimal Iterative Algorithms and Restarted Versions for Linear Matrix Equation and Pseudoinverse

open access: yesMathematics
We derive a double-optimal iterative algorithm (DOIA) in an m-degree matrix pencil Krylov subspace to solve a rectangular linear matrix equation. Expressing the iterative solution in a matrix pencil and using two optimization techniques, we determine the
Chein-Shan Liu   +2 more
doaj   +1 more source

Mean-field theory for the inverse Ising problem at low temperatures

open access: yes, 2012
The large amounts of data from molecular biology and neuroscience have lead to a renewed interest in the inverse Ising problem: how to reconstruct parameters of the Ising model (couplings between spins and external fields) from a number of spin ...
Berg, Johannes, Nguyen, H. Chau
core   +1 more source

On the Simulatability Condition in Key Generation Over a Non-authenticated Public Channel

open access: yes, 2014
Simulatability condition is a fundamental concept in studying key generation over a non-authenticated public channel, in which Eve is active and can intercept, modify and falsify messages exchanged over the non-authenticated public channel.
Lai, Lifeng, Tu, Wenwen
core   +1 more source

Computing generalized inverses using LU factorization of matrix product

open access: yes, 2011
An algorithm for computing {2, 3}, {2, 4}, {1, 2, 3}, {1, 2, 4} -inverses and the Moore-Penrose inverse of a given rational matrix A is established. Classes A(2, 3)s and A(2, 4)s are characterized in terms of matrix products (R*A)+R* and T*(AT*)+, where ...
Ben-Israel A.   +11 more
core   +1 more source

Kalman Filtering with Unknown Noise Covariances [PDF]

open access: yes, 2006
Since it is often difficult to identify the noise covariances for a Kalman filter, they are commonly considered design variables. If so, we can as well try to choose them so that the corresponding Kalman filter has some nice form.
Nilsson, Martin
core   +1 more source

Confidence Intervals in High-Dimensional Regression Based on Regularized Pseudoinverses

open access: yes, 2017
In modern data sets, the number of available variables can greatly exceed the number of observations. In this paper we show how valid confidence intervals can be constructed by approximating the inverse covariance matrix by a scaled Moore-Penrose ...
Boot, Tom, Nibbering, Didier
core   +1 more source

Convergence analysis of a proximal Gauss-Newton method

open access: yes, 2011
An extension of the Gauss-Newton algorithm is proposed to find local minimizers of penalized nonlinear least squares problems, under generalized Lipschitz assumptions.
Salzo, Saverio, Villa, Silvia
core   +2 more sources

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