Publications related to M-estimator

The regularized tau estimator: A robust and efficient solution to ill-posed linear inverse problems

Martin Vetterli, Benjamin Bejar Haro, Marta Martinez-Camara

Linear inverse problems are ubiquitous. Often the measurements do not follow a Gaussian distribution. Additionally, a model matrix with a large condition number can complicate the problem further by making it ill-posed. In this case, the performance of pop ...

2017

Parameter Determination of Sensor Stochastic Models under Covariate Dependency

Jan Skaloud, Stéphane Guerrier, Philipp Clausen

The proliferation of (low-cost) sensors provokes new challenges in data fusion. This is related to the correctness of stochastic characterization that is a prerequisite for optimal estimation of parameters from redundant observations. Different (statistica ...

2017

Correcting for photodestruction in super-resolution optical fluctuation imaging

Theo Lasser, Arno Pino Bouwens, Tomas Lukes

Super-resolution optical fluctuation imaging overcomes the diffraction limit by analyzing fluctuations in the fluorophore emission. A key assumption of the imaging is that the fluorophores are independent, though this is invalidated in the presence of phot ...

Nature Publishing Group2017

Linear Parameter-Varying Kalman Filter for angular velocity estimation of a reaction sphere actuator for satellite attitude control

Alireza Karimi, Leopoldo Rossini, Guzmán Borque Gallego

This paper presents a novel angular velocity estimation strategy of a Reaction Sphere (RS) for satellite attitude control based on a Linear Parameter-Varying (LPV) Kalman Filter. The reaction sphere is a permanent magnet synchronous spherical actuator whos ...

IEEE2017

Likelihood estimators for multivariate extremes

Anthony Christopher Davison, Raphaël Huser

The main approach to inference for multivariate extremes consists in approximating the joint upper tail of the observations by a parametric family arising in the limit for extreme events. The latter may be expressed in terms of componentwise maxima, high t ...

Springer2016

Robust compressive sensing of sparse signals: A review

Alonso Ramirez Manzanares, Rafael Eduardo Carrillo Rangel

Compressive sensing generally relies on the L2-norm for data fidelity, whereas in many applications robust estimators are needed. Among the scenarios in which robust performance is required, applications where the sampling process is performed in the prese ...

Springer International Publishing Ag2016

Frank-Wolfe Works for Non-Lipschitz Continuous Gradient Objectives: Scalable Poisson Phase Retrieval

Volkan Cevher, Quoc Tran Dinh, Alp Yurtsever, Yen-Huan Li, Ya-Ping Hsieh, Marwa El Halabi, Gergely Odor

We study a phase retrieval problem in the Poisson noise model. Motivated by the PhaseLift approach, we approximate the maximum-likelihood estimator by solving a convex program with a nuclear norm constraint. While the Frank-Wolfe algorithm, together with t ...

Ieee2016

Closed fringe demodulation using phase decomposition by Fourier basis functions

Pramod Rastogi, Rishikesh Dilip Kulkarni

We report a new technique for the demodulation of a closed fringe pattern by representing the phase as a weighted linear combination of a certain number of linearly independent Fourier basis functions in a given row/column at a time. A state space model is ...

2016

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M-estimator

The regularized tau estimator: A robust and efficient solution to ill-posed linear inverse problems

Robust Distributed Estimation by Networked Agents

Functional data analysis by matrix completion

Parameter Determination of Sensor Stochastic Models under Covariate Dependency

Correcting for photodestruction in super-resolution optical fluctuation imaging

Linear Parameter-Varying Kalman Filter for angular velocity estimation of a reaction sphere actuator for satellite attitude control

Likelihood estimators for multivariate extremes

Robust compressive sensing of sparse signals: A review

Frank-Wolfe Works for Non-Lipschitz Continuous Gradient Objectives: Scalable Poisson Phase Retrieval

Closed fringe demodulation using phase decomposition by Fourier basis functions

Graph Chatbot

Chat with Graph Search

Likelihood estimators for multivariate extremes

Correcting for photodestruction in super-resolution optical fluctuation imaging

Linear Parameter-Varying Kalman Filter for angular velocity estimation of a reaction sphere actuator for satellite attitude control

Functional data analysis by matrix completion

Robust compressive sensing of sparse signals: A review

Frank-Wolfe Works for Non-Lipschitz Continuous Gradient Objectives: Scalable Poisson Phase Retrieval

Closed fringe demodulation using phase decomposition by Fourier basis functions

Parameter Determination of Sensor Stochastic Models under Covariate Dependency

Robust Distributed Estimation by Networked Agents

The regularized tau estimator: A robust and efficient solution to ill-posed linear inverse problems