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A Multicore Convex Optimization Algorithm with Applications to Video Restoration

Citation Author(s):
Jean-Christophe Pesquet, Hugues Talbot
Submitted by:
Emilie Chouzenoux
Last updated:
8 May 2019 - 8:22am
Document Type:
Presentation Slides
Document Year:
2018
Event:
Presenters Name:
Emilie CHOUZENOUX
Paper Code:
2695

Abstract 

Abstract: 

In this paper, we present a new distributed algorithm for minimizing a sum of non-necessarily differentiable convex
functions composed with arbitrary linear operators. The overall cost function is assumed strongly convex.
Each involved function is associated with a node of a hypergraph having the ability to communicate with neighboring nodes sharing the same hyperedge. Our algorithm relies on a primal-dual splitting strategy with established convergence guarantees. We show how it can be efficiently implemented to take full advantage of a multicore architecture. The good numerical performance of the proposed approach is illustrated in a problem of video sequence denoising, where a significant speedup is achieved.

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ICIP2018poster.pdf

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