Publications related to Adaptive tracking of linear time-variant systems by extended RLS algorithms

Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity

Rachid Guerraoui, Nirupam Gupta, Youssef Allouah, Geovani Rizk, Rafaël Benjamin Pinot

The theory underlying robust distributed learning algorithms, designed to resist adversarial machines, matches empirical observations when data is homogeneous. Under data heterogeneity however, which is the norm in practical scenarios, established lower bo ...

2023

Iterative pre-conditioning for expediting the distributed gradient-descent method: The case of linear least-squares problem

Nirupam Gupta

This paper considers the multi-agent linear least-squares problem in a server-agent network architecture. The system comprises multiple agents, each with a set of local data points. The agents are connected to a server, and there is no inter-agent communic ...

PERGAMON-ELSEVIER SCIENCE LTD2022

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

Alexandre Caboussat, Dimitrios Gourzoulidis

We consider a least-squares/relaxation finite element method for the numerical solution of the prescribed Jacobian equation. We look for its solution via a least-squares approach. We introduce a relaxation algorithm that decouples this least-squares proble ...

SPRINGER/PLENUM PUBLISHERS2022

Rapid Scalable Distributed Power Flow with Open-Source Implementation

Yuning Jiang, Xinliang Dai

This paper introduces a new method for solving the distributed AC power flow (PF) problem by further exploiting the problem formulation. We propose a new variant of the ALADIN algorithm devised specifically for this type of problem. This new variant is cha ...

ELSEVIER2022

Frequency-Domain Diffusion Adaptation Over Networks

Ali H. Sayed, Ricardo Merched, Shuo Zhang

This paper analyzes the implementation of least-mean-squares (LMS)-based, adaptive diffusion algorithms over networks in the frequency-domain (FD). We focus on a scenario of noisy links and include a moving-average step for denoising after self-learning to ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Rational-based model order reduction of Helmholtz frequency response problems with adaptive finite element snapshots

Francesca Bonizzoni, Davide Pradovera

We introduce several spatially adaptive model order reduction approaches tailored to non-coercive elliptic boundary value problems, specifically, parametric-in-frequency Helmholtz problems. The offline information is computed by means of adaptive finite el ...

2021

Parameter Estimation of Three-Phase Untransposed Short Transmission Lines from Synchrophasor Measurements

Jean-Yves Le Boudec, Mario Paolone, Arpan Mukhopadhyay

We present a new approach for estimating the parameters of three-phase untransposed electrically short transmission lines using voltage/current synchrophasor measurements obtained from phasor measurement units. The parameters to be estimated are the entrie ...

2020

Basic gestalt laws cannot explain uncrowding

Michael Herzog, Oh-Hyeon Choung, Einat Rashal

Visual crowding is the inability to perceive elements within clutter. Traditional crowding models, such as pooling, predict that performance deteriorates when flankers are added. However, this prediction has been disproved. For example, performance was fou ...

SAGE PUBLICATIONS LTD2019

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

Volkan Cevher, Junhong Lin

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

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

Adaptive tracking of linear time-variant systems by extended RLS algorithms

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Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity

Iterative pre-conditioning for expediting the distributed gradient-descent method: The case of linear least-squares problem

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

Rapid Scalable Distributed Power Flow with Open-Source Implementation

Frequency-Domain Diffusion Adaptation Over Networks

Rational-based model order reduction of Helmholtz frequency response problems with adaptive finite element snapshots

Parameter Estimation of Three-Phase Untransposed Short Transmission Lines from Synchrophasor Measurements

Basic gestalt laws cannot explain uncrowding

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

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

Iterative pre-conditioning for expediting the distributed gradient-descent method: The case of linear least-squares problem

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

Frequency-Domain Diffusion Adaptation Over Networks

Parameter Estimation of Three-Phase Untransposed Short Transmission Lines from Synchrophasor Measurements

Rational-based model order reduction of Helmholtz frequency response problems with adaptive finite element snapshots

Basic gestalt laws cannot explain uncrowding

Rapid Scalable Distributed Power Flow with Open-Source Implementation

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

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

Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity