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Distributed dictionary learning over a sensor network

Pierre Chainais 1, 2, 3 Cédric Richard 4 
3 SEQUEL - Sequential Learning
LIFL - Laboratoire d'Informatique Fondamentale de Lille, Inria Lille - Nord Europe, LAGIS - Laboratoire d'Automatique, Génie Informatique et Signal
Abstract : We consider the problem of distributed dictionary learning, where a set of nodes is required to collec- tively learn a common dictionary from noisy measure- ments. This approach may be useful in several con- texts including sensor networks. Diffusion cooperation schemes have been proposed to solve the distributed linear regression problem. In this work we focus on a diffusion-based adaptive dictionary learning strategy: each node records observations and cooperates with its neighbors by sharing its local dictionary. The resulting algorithm corresponds to a distributed block coordi- nate descent (alternate optimization). Beyond dictio- nary learning, this strategy could be adapted to many matrix factorization problems and generalized to var- ious settings. This article presents our approach and illustrates its efficiency on some numerical examples.
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Submitted on : Saturday, January 4, 2014 - 12:54:50 PM
Last modification on : Tuesday, December 6, 2022 - 12:42:13 PM
Long-term archiving on: : Friday, April 4, 2014 - 10:10:28 PM


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  • HAL Id : hal-00923741, version 1


Pierre Chainais, Cédric Richard. Distributed dictionary learning over a sensor network. CaP 2013, Jul 2013, Villeneuve d'Ascq, France. pp.1-4. ⟨hal-00923741⟩



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