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Proximal operator

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

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2019
2019
Recent advances have illustrated that it is often possible to learn to solve linear inverse problems in imaging using training… 
2017
2017
In ultrasound (US) imaging, beamforming is usually separated from the deconvolution or some other post-processing techniques. The… 
2017
2017
In the past decade, sparsity-driven methods have led to substantial improvements in the capabilities of numerous imaging systems… 
2016
2016
In this paper, we propose a stochastic proximal gradient method to train ternary weight neural networks (TNN). The proposed… 
2016
2016
For the past few years, researchers hold a strong interests on knowledge-aided object-oriented high-resolution microwave imaging… 
2016
2016
In computer vision, many problems can be formulated as finding a low rank approximation of a given matrix. Ideally, if all… 
2015
2015
  • 2015
  • Corpus ID: 16441296
For completeness, in this section we derive the dual (5) to the problem of computing proximal operator for the ERM objective (3). 
2014
2014
The split Bregman (SB) method [T. Goldstein and S. Osher, SIAM J. Imaging Sci., 2 (2009), pp. 323-43] is a fast splitting-based…