Publications related to Joint Texture and Topography Estimation for Extended Depth of Field in Brightfield Microscopy

Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces

We investigate regularized algorithms combining with projection for least-squares regression problem over a Hilbert space, covering nonparametric regression over a reproducing kernel Hilbert space. We prove convergence results with respect to variants of n ...

ICML2018

Reconstruction of 3D scattered data via radial basis functions by efficient and robust techniques

Alberto Crivellaro

We propose new algorithms to overcome two of the most constraining limitations of surface reconstruction methods in use. In particular, we focus on the large amount of data characterizing standard acquisitions by scanner and the noise intrinsically introdu ...

Elsevier Science Bv2017

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

Fabio Nobile, Giovanni Migliorati

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 ...

2015

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

Afsaneh Asaei, Mohammadjavad Taghizadeh, Saeid Haghighatshoar

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 ...

2015

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

Afsaneh Asaei, Mohammadjavad Taghizadeh, Saeid Haghighatshoar

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

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

Fabio Nobile, Giovanni Migliorati

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

MATHICSE2014

Robust distributed detection over adaptive diffusion networks

Ali H. Sayed, Ali Zoubir

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

Can Localization Microscopy Benefit From Approximation Theory?

Michaël Unser, Cédric René Jean Vonesch, Hagay Kirshner

We introduce a general and computationally efficient approach to 3-D localization microscopy. The main idea is to construct a continuous-domain representation of the PSF by expanding it in a polynomial B-spline basis. This allows us to fit the PSF to the d ...

IEEE2013

Model-Based 2.5-D Deconvolution for Extended Depth of Field in Brightfield Microscopy

Michaël Unser, Dimitri Nestor Alice Van De Ville, François Aguet

Due to the limited depth of field of brightfield microscopes, it is usually impossible to image thick specimens entirely in focus. By optically sectioning the specimen, the in-focus information at the specimen's surface can be acquired over a range of imag ...

IEEE2008

Generalized linear prediction method in phase-shifting interferometry in the presence of noise

Pramod Rastogi, Abhijit Patil, Rajesh Langoju

The effectiveness of phase-shifting interferometry (PSI) techniques employing piezoelectric device PZT in the estimation of phase depends largely on the accuracy with which the phase shifts are imparted to the device and the noise influencing the measureme ...

Elsevier2007

Joint Texture and Topography Estimation for Extended Depth of Field in Brightfield Microscopy

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Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces

Reconstruction of 3D scattered data via radial basis functions by efficient and robust techniques

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

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

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

Can Localization Microscopy Benefit From Approximation Theory?

Model-Based 2.5-D Deconvolution for Extended Depth of Field in Brightfield Microscopy

Generalized linear prediction method in phase-shifting interferometry in the presence of noise

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

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

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

Reconstruction of 3D scattered data via radial basis functions by efficient and robust techniques

Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces

Robust distributed detection over adaptive diffusion networks

Model-Based 2.5-D Deconvolution for Extended Depth of Field in Brightfield Microscopy

Can Localization Microscopy Benefit From Approximation Theory?

Generalized linear prediction method in phase-shifting interferometry in the presence of noise