# Proximal operator

## Papers overview

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2018

2018

- J. Sci. Comput.
- 2018

This paper aims to develop new and fast algorithms for recovering a sparse vector from a small number of measurements, which is aâ€¦Â (More)

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2018

2018

- ArXiv
- 2018

In this work, we broadly connect kernel-based filtering (e.g. approaches such as the bilateral filters and nonlocal means, butâ€¦Â (More)

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2017

2017

- 2017 IEEE International Conference on Computerâ€¦
- 2017

While variational methods have been among the most powerful tools for solving linear inverse problems in imaging, deepâ€¦Â (More)

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2016

2016

- ArXiv
- 2016

In this paper, we propose a stochastic proximal gradient method to train ternary weight neural networks (TNN). The proposedâ€¦Â (More)

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2016

2016

- ArXiv
- 2016

Quadratic-support functions [Aravkin, Burke, and Pillonetto; J. Mach. Learn. Res. 14(1), 2013] constitute a parametric family ofâ€¦Â (More)

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2015

2015

- Neural Computation
- 2015

We present a fast, efficient algorithm for learning an overcomplete dictionary for sparse representation of signals. The wholeâ€¦Â (More)

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Highly Cited

2014

Highly Cited

2014

- NIPS
- 2014

In this work we introduce a new optimisation method called SAGA in the spirit of SAG, SDCA, MISO and SVRG, a set of recentlyâ€¦Â (More)

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2012

2012

- 2012 50th Annual Allerton Conference onâ€¦
- 2012

We present a distributed proximal-gradient method for optimizing the average of convex functions, each of which is the privateâ€¦Â (More)

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Highly Cited

2011

Highly Cited

2011

- Journal of Machine Learning Research
- 2011

Sparse coding consists in representing signals as sparse li near combinations of atoms selected from a dictionary. We consider anâ€¦Â (More)

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2010

Highly Cited

2010

- ICML
- 2010

We propose to combine two approaches for modeling data admitting sparse representations: on the one hand, dictionary learning hasâ€¦Â (More)

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