Publications related to Gabor dual windows using convex optimization

A Data-Driven Method for Computing Fixed-Structure Low-Order Controllers With H∞ Performance

Recently, a new data-driven method for robust control with H ∞ performance has been proposed. This method is based on convex optimization and converges to the optimal performance when the controller order increases. However, for low-order controllers, the ...

2018

Proximity Operators of Discrete Information Divergences

Mireille El Gheche, Giovanni Chierchia

While phi-divergences have been extensively studied in convex analysis, their use in optimization problems often remains challenging. In this regard, one of the main shortcomings of existing methods is that the minimization of phi-divergences is usually pe ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018

Fast and robust estimation of NODDI parameters using non-Gaussian noise models and spatial regularization

Jean-Philippe Thiran, Erick Jorge Canales Rodriguez, Alessandro Daducci

In this study, we developed a robust inversion algorithm to estimate the Neurite Orientation Dispersion and Density Imaging (NODDI) model. It is based on the Accelerated Microstructure Imaging via Convex Optimization (AMICO) framework. However, in contrast ...

2018

A Data-Driven Approach to Power Converter Control via Convex Optimization

Alireza Karimi, Achille Nicoletti, Michele Martino

A new model reference data-driven approach is presented for synthesizing controllers for the CERN power converter control system. This method uses the frequency re- sponse function (FRF) of a system in order to avoid the problem of unmodeled dynamics assoc ...

2017

Why CLEAN when you can PURIFY? A new approach for next-generation radio-interferometric imaging

Yves Wiaux, Rafael Eduardo Carrillo Rangel, Jason Douglas McEwen

In recent works, sparse models and convex optimization techniques have been applied to radio-interferometric (RI) imaging showing the potential to outperform state-of-the-art imaging algorithms in the field. In this talk, I will review our latest contribut ...

2015

A Data-Driven Approach in Designing RST Controllers with H∞ Performance via Convex Optimization

Alireza Karimi, Achille Nicoletti, Zlatko Emedi

In this paper, a new method for designing robust fixed-order

\mathcal{H}_{\infty}

discrete-time controllers is presented. The controller structure is a two-degree of freedom polynomial controller of the

RST

type. A data-driven approach is implemented f ...

IEEE2015

Composite convex minimization involving self-concordant-like cost functions

Volkan Cevher, Quoc Tran Dinh, Yen-Huan Li

Abstract. The self-concordant-like property of a smooth convex func- tion is a new analytical structure that generalizes the self-concordant notion. While a wide variety of important applications feature the self- concordant-like property, this concept has ...

2015

Composite convex minimization involving self-concordant-like cost functions

Volkan Cevher, Quoc Tran Dinh, Yen-Huan Li

The self-concordant-like property of a smooth convex func- tion is a new analytical structure that generalizes the self-concordant notion. While a wide variety of important applications feature the self- concordant-like property, this concept has heretofor ...

2015

Convex Optimization for Big Data

Volkan Cevher

This article reviews recent advances in convex optimization algorithms for Big Data, which aim to reduce the computational, storage, and communications bottlenecks. We provide an overview of this emerging field, describe contemporary approximation techniqu ...

Institute of Electrical and Electronics Engineers2014

PURIFY: A new algorithmic framework for next-generation radio-interferometric imaging

Yves Wiaux, Rafael Eduardo Carrillo Rangel, Jason Douglas McEwen

In recent works, compressed sensing (CS) and convex opti- mization techniques have been applied to radio-interferometric imaging showing the potential to outperform state-of-the-art imaging algorithms in the field. We review our latest contributions [1, 2, ...

Ieee2014

Gabor dual windows using convex optimization

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A Data-Driven Method for Computing Fixed-Structure Low-Order Controllers With H∞ Performance

Proximity Operators of Discrete Information Divergences

Fast and robust estimation of NODDI parameters using non-Gaussian noise models and spatial regularization

A Data-Driven Approach to Power Converter Control via Convex Optimization

Why CLEAN when you can PURIFY? A new approach for next-generation radio-interferometric imaging

A Data-Driven Approach in Designing RST Controllers with H∞ Performance via Convex Optimization

Composite convex minimization involving self-concordant-like cost functions

Composite convex minimization involving self-concordant-like cost functions

Convex Optimization for Big Data

PURIFY: A new algorithmic framework for next-generation radio-interferometric imaging

Fast and robust estimation of NODDI parameters using non-Gaussian noise models and spatial regularization

A Data-Driven Method for Computing Fixed-Structure Low-Order Controllers With H∞ Performance

A Data-Driven Approach to Power Converter Control via Convex Optimization

Proximity Operators of Discrete Information Divergences

Convex Optimization for Big Data

A Data-Driven Approach in Designing RST Controllers with H∞ Performance via Convex Optimization

PURIFY: A new algorithmic framework for next-generation radio-interferometric imaging

Why CLEAN when you can PURIFY? A new approach for next-generation radio-interferometric imaging

Composite convex minimization involving self-concordant-like cost functions

Composite convex minimization involving self-concordant-like cost functions