Publications related to Locally convex topological vector space

Variational Decomposition of Vector Fields in the Presence of Noise

Michaël Unser, Emrah Bostan, Pouya Dehghani Tafti

We present a variational framework, and an algorithm based on the alternating method of multipliers (ADMM), for the problem of decomposing a vector field into its curl- and divergence-free components (Helmholtz decomposition) in the presence of noise. We p ...

IEEE2013

Fixed-order LPV Controller Design for LPV Systems by Convex Optimization

Alireza Karimi, Zlatko Emedi

In this paper a new method for fixed-order output-feedback Linear Parameter Varying (LPV) controller design is presented. First, a set of stabilizing LPV controllers is given as an inner convex approximation of the non-convex set of all stabilizing LPV con ...

2013

A hybrid model predictive control scheme for containment and distributed sensing in multi-agent systems

Giancarlo Ferrari Trecate

This paper proposes a control scheme for distributed sensing using a leader/follower multi-agent architecture. The control objective is to make a group of mobile agents cover and sense a sequence of regions of interest. More specifically, when the leaders ...

2013

To Convexify or Not? Regression with Clustering Penalties on Graphs

Volkan Cevher, Luca Baldassarre, Marwa El Halabi

We consider minimization problems that are compositions of convex functions of a vector

\x \in\reals^N

with submodular set functions of its support (i.e., indices of the non-zero coefficients of

\x

). Such problems are in general difficult for large

N

...

IEEE2013

A convex optimization framework for global tractography

Jean-Philippe Thiran, Alessandro Daducci, Alia Lemkaddem

In this article we present a novel approach for diffusion MRI global tractography. Our formulation models the signal in each voxel as a linear combination of fiber-tract basis func- tions, which consist of a comprehensive set of plausible fiber tracts that ...

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

Approaches to Conditional Risk

Damir Filipovic

We present and compare two different approaches to conditional risk measures. One approach draws from convex analysis in vector spaces and presents risk measures as functions on Lp spaces, while the other approach utilizes module-based convex analysis wher ...

2012

JOINT TRACE/TV NORM MINIMIZATION: A NEW EFFICIENT APPROACH FOR SPECTRAL COMPRESSIVE IMAGING

Pierre Vandergheynst, Mohammad Golbabaee

In this paper we propose a novel and efficient model for compressed sensing of hyperspectral images. A large-size hyperspectral image can be subsampled by retaining only 3% of its original size, yet robustly recovered using the new approach we present here ...

2012

Matrix ALPS: Accelerated Low Rank and Sparse Matrix Reconstruction

Volkan Cevher, Anastasios Kyrillidis

We propose Matrix ALPS for recovering a sparse plus low-rank decomposition of a matrix given its corrupted and incomplete linear measurements. Our approach is a first-order projected gradient method over non-convex sets, and it exploits a well-known memory ...

IEEE2012

Tight lower bounds for the size of epsilon-nets

János Pach, Gábor Tardos

According to a well known theorem of Haussler and Welzl (1987), any range space of bounded VC-dimension admits an epsilon-net of size O (1/epsilon log 1/epsilon). Using probabilistic techniques, Pach and Woeginger (1990) showed that there exist range space ...

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Locally convex topological vector space

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Variational Decomposition of Vector Fields in the Presence of Noise

Fixed-order LPV Controller Design for LPV Systems by Convex Optimization

A hybrid model predictive control scheme for containment and distributed sensing in multi-agent systems

To Convexify or Not? Regression with Clustering Penalties on Graphs

A convex optimization framework for global tractography

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

Approaches to Conditional Risk

JOINT TRACE/TV NORM MINIMIZATION: A NEW EFFICIENT APPROACH FOR SPECTRAL COMPRESSIVE IMAGING

Matrix ALPS: Accelerated Low Rank and Sparse Matrix Reconstruction

Tight lower bounds for the size of epsilon-nets

Fixed-order LPV Controller Design for LPV Systems by Convex Optimization

Variational Decomposition of Vector Fields in the Presence of Noise

To Convexify or Not? Regression with Clustering Penalties on Graphs

A hybrid model predictive control scheme for containment and distributed sensing in multi-agent systems

A convex optimization framework for global tractography

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

Approaches to Conditional Risk

JOINT TRACE/TV NORM MINIMIZATION: A NEW EFFICIENT APPROACH FOR SPECTRAL COMPRESSIVE IMAGING

Matrix ALPS: Accelerated Low Rank and Sparse Matrix Reconstruction

Tight lower bounds for the size of epsilon-nets