Publications associées à Adaptation in Stochastic Algorithms: From Nonsmooth Optimization to Min-Max Problems and Beyond

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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

Adaptation in Stochastic Algorithms: From Nonsmooth Optimization to Min-Max Problems and Beyond

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Chattez avec Graph Search

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

Inner approximations of the region of attraction for polynomial dynamical systems

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

Adaptive stochastic convex optimization over networks

Non-convex optimization for robust multi-view imaging

Non-convex optimization for robust multi-view imaging

Probabilistic inverse reinforcement learning in unknown environments

Design and operations of gas transmission networks

Fast Proximal Algorithms For Self-Concordant Function Minimization With Application To Sparse Graph Selection

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

Probabilistic inverse reinforcement learning in unknown environments

Inner approximations of the region of attraction for polynomial dynamical systems

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

Non-convex optimization for robust multi-view imaging

Design and operations of gas transmission networks

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

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

Non-convex optimization for robust multi-view imaging

Adaptive stochastic convex optimization over networks

Fast Proximal Algorithms For Self-Concordant Function Minimization With Application To Sparse Graph Selection