Search Results for author: Luca Baldassarre

Found 6 papers, 0 papers with code

Convex block-sparse linear regression with expanders -- provably

no code implementations21 Mar 2016 Anastasios Kyrillidis, Bubacarr Bah, Rouzbeh Hasheminezhad, Quoc Tran-Dinh, Luca Baldassarre, Volkan Cevher

Our experimental findings on synthetic and real applications support our claims for faster recovery in the convex setting -- as opposed to using dense sensing matrices, while showing a competitive recovery performance.

regression

Learning-based Compressive Subsampling

no code implementations21 Oct 2015 Luca Baldassarre, Yen-Huan Li, Jonathan Scarlett, Baran Gözcü, Ilija Bogunovic, Volkan Cevher

In this paper, we instead take a principled learning-based approach in which a \emph{fixed} index set is chosen based on a set of training signals $\mathbf{x}_1,\dotsc,\mathbf{x}_m$.

Combinatorial Optimization

Structured Sparsity: Discrete and Convex approaches

no code implementations20 Jul 2015 Anastasios Kyrillidis, Luca Baldassarre, Marwa El-Halabi, Quoc Tran-Dinh, Volkan Cevher

For each, we present the models in their discrete nature, discuss how to solve the ensuing discrete problems and then describe convex relaxations.

Compressive Sensing

Group-Sparse Model Selection: Hardness and Relaxations

no code implementations13 Mar 2013 Luca Baldassarre, Nirav Bhan, Volkan Cevher, Anastasios Kyrillidis, Siddhartha Satpathi

Group-based sparsity models are proven instrumental in linear regression problems for recovering signals from much fewer measurements than standard compressive sensing.

Compressive Sensing model +1

Modelling transition dynamics in MDPs with RKHS embeddings

no code implementations18 Jun 2012 Steffen Grunewalder, Guy Lever, Luca Baldassarre, Massi Pontil, Arthur Gretton

For policy optimisation we compare with least-squares policy iteration where a Gaussian process is used for value function estimation.

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