Luca Baldassarre

Cette personne n’est plus à l’EPFL

Publications associées (15)

À propos
Confidentialité
Mentions légales

Graph Chatbot

Model-based Sketching and Recovery with Expanders

Volkan Cevher, Luca Baldassarre, Bubacarr Bah

Linear sketching and recovery of sparse vectors with randomly constructed sparse matrices has numerous applications in several areas, including compressive sensing, data stream computing, graph sketching, and combinatorial group testing. This paper conside ...

2014

MAP Estimation for Bayesian Mixture Models with Submodular Priors

Volkan Cevher, Luca Baldassarre, Marwa El Halabi

We propose a Bayesian approach where the signal structure can be represented by a mixture model with a submodular prior. We consider an observation model that leads to Lipschitz functions. Due to its combinatorial nature, computing the maximum a posteriori ...

2014

Accelerated And Inexact Forward-Backward Algorithms

Luca Baldassarre

We propose a convergence analysis of accelerated forward-backward splitting methods for composite function minimization, when the proximity operator is not available in closed form, and can only be computed up to a certain precision. We prove that the 1/k( ...

Siam Publications2013

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

Tractability of interpretability via selection of group-sparse models

Volkan Cevher, Luca Baldassarre, Nirav Bhan

Group-based sparsity models are proven instrumental in linear regression problems for recovering signals from much fewer measurements than standard compressive sensing. A promise of these models is to lead to “interpretable” signals for which we identify i ...

2013

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\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