Proximal operator

In mathematical optimization, the proximal operator is an operator associated with a convex function defined by: It is frequently used in… (More)
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Papers overview

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2018
2018
This paper aims to develop new and fast algorithms for recovering a sparse vector from a small number of measurements, which is a… (More)
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2018
2018
In this work, we broadly connect kernel-based filtering (e.g. approaches such as the bilateral filters and nonlocal means, but… (More)
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2017
2017
While variational methods have been among the most powerful tools for solving linear inverse problems in imaging, deep… (More)
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2016
2016
In this paper, we propose a stochastic proximal gradient method to train ternary weight neural networks (TNN). The proposed… (More)
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2016
2016
Quadratic-support functions [Aravkin, Burke, and Pillonetto; J. Mach. Learn. Res. 14(1), 2013] constitute a parametric family of… (More)
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2015
2015
We present a fast, efficient algorithm for learning an overcomplete dictionary for sparse representation of signals. The whole… (More)
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Highly Cited
2014
Highly Cited
2014
In this work we introduce a new optimisation method called SAGA in the spirit of SAG, SDCA, MISO and SVRG, a set of recently… (More)
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2012
2012
We present a distributed proximal-gradient method for optimizing the average of convex functions, each of which is the private… (More)
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Highly Cited
2011
Highly Cited
2011
Sparse coding consists in representing signals as sparse li near combinations of atoms selected from a dictionary. We consider an… (More)
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Highly Cited
2010
Highly Cited
2010
We propose to combine two approaches for modeling data admitting sparse representations: on the one hand, dictionary learning has… (More)
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