Publications related to Composite convex minimization involving self-concordant-like cost functions

Regularity results for very degenerate elliptic equations

We consider a family of elliptic equations introduced in the context of traffic congestion. They have the form del . (del F(del u)) = f where F is a convex function which vanishes inside some convex set and is elliptic outside. Under some natural assumptio ...

2014

A global existence result for the semigeostrophic equations in three dimensional convex domains

Maria Colombo

Exploiting recent regularity estimates for the Monge-Ampère equation, under some suitable assumptions on the initial data we prove global-in-time existence of Eulerian distributional solutions to the semigeostrophic equations in 3-dimensional convex domain ...

2014

A Global Existence Result for the Semigeostrophic Equations in Three Dimensional Convex Domains

Maria Colombo

Exploiting recent regularity estimates for the Monge-Ampere equation, under some suitable assumptions on the initial data we prove global in-time existence of Eulerian distributional solutions to the semigeostrophic equations in 3-dimensional convex domain ...

2014

A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions

Volkan Cevher, Quoc Tran Dinh, Anastasios Kyrillidis

We propose an algorithmic framework for convex minimization problems of a composite function with two terms: a self-concordant function and a possibly nonsmooth regularization term. Our method is a new proximal Newton algorithm that features a local quadra ...

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

Time-Optimal Path Following for Robots With Convex-Concave Constraints Using Sequential Convex Programming

Quoc Tran Dinh

Time-optimal path following considers the problem of moving along a predetermined geometric path in minimum time. In the case of a robotic manipulator with simplified constraints, a convex reformulation of this optimal control problem has been derived prev ...

Institute of Electrical and Electronics Engineers2013

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

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

Fast Proximal algorithms for Self-concordant function minimization with application to sparse graph selection

Volkan Cevher, Anastasios Kyrillidis

The convex

\ell_1

-regularized

\log\det

divergence criterion has been shown to produce theoretically consistent graph learning. However, this objective function is challenging since the

\ell_1

-regularization is nonsmooth, the

\log\det

objective is n ...

2013

Composite convex minimization involving self-concordant-like cost functions

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Regularity results for very degenerate elliptic equations

A global existence result for the semigeostrophic equations in three dimensional convex domains

A Global Existence Result for the Semigeostrophic Equations in Three Dimensional Convex Domains

A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions

Blind Sensor Calibration in Sparse Recovery Using Convex Optimization

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

Time-Optimal Path Following for Robots With Convex-Concave Constraints Using Sequential Convex Programming

Gabor dual windows using convex optimization

To Convexify or Not? Regression with Clustering Penalties on Graphs

Fast Proximal algorithms for Self-concordant function minimization with application to sparse graph selection

A Global Existence Result for the Semigeostrophic Equations in Three Dimensional Convex Domains

A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions

A global existence result for the semigeostrophic equations in three dimensional convex domains

Regularity results for very degenerate elliptic equations

Blind Sensor Calibration in Sparse Recovery Using Convex Optimization

Time-Optimal Path Following for Robots With Convex-Concave Constraints Using Sequential Convex Programming

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

Gabor dual windows using convex optimization

To Convexify or Not? Regression with Clustering Penalties on Graphs

Fast Proximal algorithms for Self-concordant function minimization with application to sparse graph selection