Publications related to Support Recovery in Compressed Sensing: An Estimation Theoretic Approach

Limits on Support Recovery With Probabilistic Models: An Information-Theoretic Framework

The support recovery problem consists of determining a sparse subset of a set of variables that is relevant in generating a set of observations, and arises in a diverse range of settings, such as compressive sensing, subset selection in regression, and gro ...

Institute of Electrical and Electronics Engineers2017

Long-Term Stable Control of Motor-Imagery BCI by a Locked-in User Through Adaptive Assistance

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Sareh Saeedi

Performance variation is one of the main challenges that BCIs are confronted with, when being used over extended periods of time. Shared control techniques could partially cope with such a problem. In this paper, we propose a taxonomy of shared control app ...

Institute of Electrical and Electronics Engineers2017

A smartphone application to determine body length for body weight estimation in children: a prospective clinical trial.

Davide Scaramuzza

The aim of this study was to test the feasibility and accuracy of a smartphone application to measure the body length of children using the integrated camera and to evaluate the subsequent weight estimates. A prospective clinical trial of children aged 0–< ...

Springer Verlag2017

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

Evaluation of ICA-Based ICTD for PolSAR Data Analysis Using a Sliding Window Approach: Convergence Rate, Gaussian Sources, and Spatial Correlation

Nikola Besic

Polarimetric incoherent target decomposition aims at accessing physical parameters of illuminated scatters through the analysis of the target coherence or covariance matrix. In this framework, independent component analysis (ICA) was recently proposed as a ...

Institute of Electrical and Electronics Engineers2016

Estimation Error of the Constrained Lasso

Volkan Cevher, Yen-Huan Li, Ya-Ping Hsieh, Nissim Zerbib

This paper presents a non-asymptotic upper bound for the estimation error of the constrained lasso, under the high-dimensional (

n \ll p

) setting. In contrast to existing results, the error bound in this paper is sharp, is valid when the parameter to be e ...

2016

Adaptive Assistance for Brain-Computer Interfaces by Online Prediction of Command Reliability

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Robert Leeb, Sareh Saeedi

One of the challenges of using brain-computer interfaces (BCIs) over extended periods of time is the variation of the users' performance across different experimental days. The goal of the current study is to propose a performance estimator for an electroe ...

Institute of Electrical and Electronics Engineers2016

A new robust and efficient estimator for ill-conditioned linear inverse problems with outliers

Martin Vetterli, Ali Zoubir, Marta Martinez-Camara

Solving a linear inverse problem may include difficulties such as the presence of outliers and a mixing matrix with a large condition number. In such cases a regularized robust estimator is needed. We propose a new tau-type regularized robust estimator tha ...

2015

Sparsity-Driven Statistical Inference for Inverse Problems

Ulugbek Kamilov

This thesis addresses statistical inference for the resolution of inverse problems. Our work is motivated by the recent trend whereby classical linear methods are being replaced by nonlinear alternatives that rely on the sparsity of naturally occurring sig ...

EPFL2015

Designing Statistical Estimators That Balance Sample Size, Risk, and Computational Cost

Volkan Cevher

This paper proposes a tradeoff between computational time, sample complexity, and statistical accuracy that applies to statistical estimators based on convex optimization. When we have a large amount of data, we can exploit excess samples to decrease stati ...

Ieee-Inst Electrical Electronics Engineers Inc2015

Support Recovery in Compressed Sensing: An Estimation Theoretic Approach

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Limits on Support Recovery With Probabilistic Models: An Information-Theoretic Framework

Long-Term Stable Control of Motor-Imagery BCI by a Locked-in User Through Adaptive Assistance

A smartphone application to determine body length for body weight estimation in children: a prospective clinical trial.

Robust compressive sensing of sparse signals: A review

Evaluation of ICA-Based ICTD for PolSAR Data Analysis Using a Sliding Window Approach: Convergence Rate, Gaussian Sources, and Spatial Correlation

Estimation Error of the Constrained Lasso

Adaptive Assistance for Brain-Computer Interfaces by Online Prediction of Command Reliability

A new robust and efficient estimator for ill-conditioned linear inverse problems with outliers

Sparsity-Driven Statistical Inference for Inverse Problems

Designing Statistical Estimators That Balance Sample Size, Risk, and Computational Cost

A smartphone application to determine body length for body weight estimation in children: a prospective clinical trial.

Estimation Error of the Constrained Lasso

A new robust and efficient estimator for ill-conditioned linear inverse problems with outliers

Robust compressive sensing of sparse signals: A review

Evaluation of ICA-Based ICTD for PolSAR Data Analysis Using a Sliding Window Approach: Convergence Rate, Gaussian Sources, and Spatial Correlation

Adaptive Assistance for Brain-Computer Interfaces by Online Prediction of Command Reliability

Designing Statistical Estimators That Balance Sample Size, Risk, and Computational Cost

Sparsity-Driven Statistical Inference for Inverse Problems

Limits on Support Recovery With Probabilistic Models: An Information-Theoretic Framework

Long-Term Stable Control of Motor-Imagery BCI by a Locked-in User Through Adaptive Assistance