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Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14)

2 October 2014
Laurent Jacques
C. De Vleeschouwer
Y. Boursier
Prasad Sudhakar
C. D. Mol
A. Pižurica
S. Anthoine
P. Vandergheynst
P. Frossard
Cagdas Bilen
Srdan Kitic
N. Bertin
R. Gribonval
Nicolas Boumal
Bamdev Mishra
P.-A. Absil
R. Sepulchre
Shaun Bundervoet
C. Schretter
A. Dooms
P. Schelkens
Olivier Chabiron
F. Malgouyres
J. Tourneret
N. Dobigeon
P. Chainais
C. Richard
Bruno Cornelis
Ingrid Daubechies
David B. Dunson
M. Danková
P. Rajmic
Kévin Degraux
V. Cambareri
B. Geelen
G. Lafruit
G. Setti
J. Determe
J. Louveaux
F. Horlin
Angélique Dremeau
P. Héas
Cédric Herzet
V. Duval
Gabriel Peyré
Alhussein Fawzi
M. Davies
Nicolas Gillis
S. Vavasis
C. Soussen
Luc Le Magoarou
Jingwei Liang
M. Fadili
Antoine Liutkus
D. Martina
S. Gigan
L. Daudet
Mauro Maggioni
Stanislav Minsker
Nate Strawn
C. Mory
Fred-Maurice Ngole-Mboula
Jean-Luc Starck
I. Loris
Samuel Vaiter
Mohammad Golbabaee
D. Vukobratović
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Abstract

The implicit objective of the biennial "international - Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST) is to foster collaboration between international scientific teams by disseminating ideas through both specific oral/poster presentations and free discussions. For its second edition, the iTWIST workshop took place in the medieval and picturesque town of Namur in Belgium, from Wednesday August 27th till Friday August 29th, 2014. The workshop was conveniently located in "The Arsenal" building within walking distance of both hotels and town center. iTWIST'14 has gathered about 70 international participants and has featured 9 invited talks, 10 oral presentations, and 14 posters on the following themes, all related to the theory, application and generalization of the "sparsity paradigm": Sparsity-driven data sensing and processing; Union of low dimensional subspaces; Beyond linear and convex inverse problem; Matrix/manifold/graph sensing/processing; Blind inverse problems and dictionary learning; Sparsity and computational neuroscience; Information theory, geometry and randomness; Complexity/accuracy tradeoffs in numerical methods; Sparsity? What's next?; Sparse machine learning and inference.

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