Publications related to Combinatorial Penalties: Which structures are preserved by convex relaxations?

Designing Gabor windows using convex optimization

Redundant Gabor frames admit an infinite number of dual frames, yet only the canonical dual Gabor system, constructed from the minimal l(2)-norm dual window, is widely used. This window function however, might lack desirable properties, e. g. good time-fre ...

ELSEVIER SCIENCE INC2018

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

Yield prediction in parallel homogeneous assembly

Massimo Mastrangeli, Metin Sitti

We investigate the parallel assembly of two-dimensional, geometrically-closed modular target structures out of homogeneous sets of macroscopic components of varying anisotropy. The yield predicted by a chemical reaction network (CRN)-based model is quantit ...

Royal Society of Chemistry2017

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

Michaël Unser, Martin Kurt Storath

We consider

L ^{ 1 }

-TV regularization of univariate signals with values on the real line or on the unit circle. While the real data space leads to a convex optimization problem, the problem is nonconvex for circle-valued data. In this paper, we deriv ...

SIAM2016

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

Learning with tensors: a framework based on convex optimization and spectral regularization

Quoc Tran Dinh

We present a framework based on convex optimization and spectral regularization to perform learning when feature observations are multidimensional arrays (tensors). We give a mathematical characterization of spectral penalties for tensors and analyze a uni ...

Springer2014

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

Convex computation of the region of attraction of polynomial control systems

Milan Korda

We address the long-standing problem of computing the region of attraction (ROA) of a target set (typically a neighborhood of an equilibrium point) of a controlled nonlinear system with polynomial dynamics and semialgebraic state and input constraints. We ...

Institute of Electrical and Electronics Engineers2014

Energy Efficient Collaborative Beamforming in Wireless Sensor Networks

Energy efficiency is a major design issue in the context of Wireless Sensor Networks (WSN). If the acquired data is to be sent to a far-away base station, collaborative beamforming performed by the sensors may help to distribute the communication load amon ...

Ieee-Inst Electrical Electronics Engineers Inc2014

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

Combinatorial Penalties: Which structures are preserved by convex relaxations?

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Designing Gabor windows using convex optimization

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

Yield prediction in parallel homogeneous assembly

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

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

Learning with tensors: a framework based on convex optimization and spectral regularization

Convex Optimization for Big Data

Convex computation of the region of attraction of polynomial control systems

Energy Efficient Collaborative Beamforming in Wireless Sensor Networks

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

Energy Efficient Collaborative Beamforming in Wireless Sensor Networks

Learning with tensors: a framework based on convex optimization and spectral regularization

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

Designing Gabor windows using convex optimization

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

Yield prediction in parallel homogeneous assembly

Convex computation of the region of attraction of polynomial control systems

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

Convex Optimization for Big Data