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, LAGIS - Laboratoire d'Automatique, Génie Informatique et Signal, Inria Lille - Nord Europe
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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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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