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Designing Gabor windows using convex optimization

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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

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

Gabor dual windows using convex optimization

Nathanaël Perraudin

Redundant Gabor frames admit an infinite number of dual frames, yet only the canonical dual Gabor system, con- structed from the minimal l2-norm dual window, is widely used. This window function however, might lack desirable properties, such as good time-f ...

2013

Blind Sensor Calibration in Sparse Recovery Using Convex Optimization

Rémi Gribonval, Gilles Puy

We investigate a compressive sensing system in which the sensors introduce a distortion to the measurements in the form of unknown gains. We focus on blind calibration, using measures performed on a few unknown (but sparse) signals. We extend our earlier s ...

2013

A convex optimization approach for image recovery from nonlinear measurements in optical interferometry

Yves Wiaux, Rafael Eduardo Carrillo Rangel, Anna Auria Rasclosa

Image recovery in optical interferometry is an ill-posed nonlinear inverse problem arising from incomplete power spectrum and bi-spectrum measurements. We formulate a linear version of the problem for the order-3 tensor formed by the tensor product of the ...

2013

Blind Sensor Calibration in Sparse Recovery

Rémi Gribonval, Gilles Puy

We consider the problem of calibrating a compressed sensing measurement system under the assumption that the decalibration consists of unknown complex gains on each measure. We focus on blind calibration, using measures performed on a few unknown (but spar ...

2013

Direct data-driven design of sparse controllers

Alireza Karimi

This paper deals with direct data-driven design of model-reference controllers whose number of parameters is constrained. Input-output (I/O) sparse controllers are introduced and proposed as an alternative to low-order controller tuning. The optimal I/O sp ...

IEEE2013

Regularized Bundle Methods for Convex and Non-Convex Risks

Machine learning is most often cast as an optimization problem. Ideally, one expects a convex objective function to rely on efficient convex optimizers with nice guarantees such as no local optima. Yet, non-convexity is very frequent in practice and it may ...

2012

FAST TV-L1 OPTICAL FLOW FOR INTERACTIVITY

Pierre Vandergheynst, Gilles Puy, Emmanuel D'Angelo, Johann Paratte

Vision is a natural tool for human-computer interaction, since it pro- vides visual feedback to the user and mimics some human behaviors. It requires however the fast and robust computation of motion primi- tives, which remains a difficult problem. In this ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011

A Fast Wavelet-Based Reconstruction Method for Magnetic Resonance Imaging

Michaël Unser, Matthieu Guerquin-Kern

In this work, we exploit the fact that wavelets can represent magnetic resonance images well, with relatively few coefficients. We use this property to improve magnetic resonance imaging (MRI) reconstructions from undersampled data with arbitrary k-space t ...

Institute of Electrical and Electronics Engineers2011