Publications related to A Least-Squares Method for the Solution of the Non-smooth Prescribed Jacobian Equation

MMSE Denoising of Sparse and Non-Gaussian AR(1) Processes

Michaël Unser, Emrah Bostan, Pedram Pad, Pouria Tohidi

We propose two minimum-mean-square-error (MMSE) estimation methods for denoising non-Gaussian first-order autoregressive (AR(1)) processes. The first one is based on the message passing framework and gives the exact theoretic MMSE estimator. The second is ...

IEEE2016

Definition and assessment of reference values for PMU calibration in static and transient conditions

Mario Paolone, Guglielmo Frigo, Marco Pignati, Daniele Colangelo

The calibration of Phasor Measurement Units (PMUs) consists of comparing Coordinated Universal Time (UTC) time-stamped phasors (synchrophasors) estimated by the PMU under test, against reference synchrophasors generated through a PMU calibrator. The IEEE S ...

IEEE2016

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

From averaging to acceleration, there is only a step-size

Nicolas Henri Bernard Flammarion

We consider the optimization of a quadratic objective function whose gradients are only accessible through a stochastic oracle that returns the gradient at any given point plus a zero-mean finite variance random error. We present the first algorithm that a ...

2015

Linearized numerical homogenization method for nonlinear monotone parabolic multiscale problems

Assyr Abdulle, Gilles Vilmart, Martin Ernst Huber

We introduce and analyze an efficient numerical homogenization method for a class of nonlinear parabolic problems of monotone type in highly oscillatory media. The new scheme avoids costly Newton iterations and is linear at both the macroscopic and the mic ...

Siam Publications2015

A Universal Primal-Dual Convex Optimization Framework

Volkan Cevher, Quoc Tran Dinh, Alp Yurtsever

We propose a new primal-dual algorithmic framework for a prototypical con- strained convex optimization template. The algorithmic instances of our frame- work are universal since they can automatically adapt to the unknown Ho ̈lder con- tinuity properties ...

2015

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

Certification of fixed computation time first-order optimization-based controllers for a class of nonlinear dynamical systems

Colin Neil Jones, Milan Korda

This paper proposes a stability verification method for systems controlled by an early terminated first-order method (e.g., an MPC problem approximately solved by a fixed number of iterations of the fast gradient method). The method is based on the observa ...

Ieee2014

A Least-Squares Method for the Solution of the Non-smooth Prescribed Jacobian Equation

Graph Chatbot

Chat with Graph Search

MMSE Denoising of Sparse and Non-Gaussian AR(1) Processes

Definition and assessment of reference values for PMU calibration in static and transient conditions

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

From averaging to acceleration, there is only a step-size

Linearized numerical homogenization method for nonlinear monotone parabolic multiscale problems

A Universal Primal-Dual Convex Optimization Framework

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

Certification of fixed computation time first-order optimization-based controllers for a class of nonlinear dynamical systems

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

MMSE Denoising of Sparse and Non-Gaussian AR(1) Processes

Definition and assessment of reference values for PMU calibration in static and transient conditions

From averaging to acceleration, there is only a step-size

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

Certification of fixed computation time first-order optimization-based controllers for a class of nonlinear dynamical systems

Linearized numerical homogenization method for nonlinear monotone parabolic multiscale problems

A Universal Primal-Dual Convex Optimization Framework

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