Regularization by spectral filtering

Spectral regularization is any of a class of regularization techniques used in machine learning to control the impact of noise and prevent… (More)
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Topic mentions per year

Topic mentions per year

1988-2016
02419882016

Papers overview

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2017
2017
We present a method for transferring neural representations from label-rich source domains to unlabeled target domains. Recent… (More)
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2017
2017
We treat the estimation of a sparse set of sources emitting plane waves observed by a sensor array as a complex-valued LASSO (c… (More)
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2017
2017
We propose a regularization function for hyperspectral image restoration based on a newly-designed structure tensor. We adopt a… (More)
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2015
2015
Large-scale sparse recovery (SR) by solving ℓ1-norm relaxations over Big Dictionary is a very challenging task. Plenty of greedy… (More)
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2014
2014
Minimization of the training regularization term has been recognized as an important objective for sparse modeling and… (More)
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2012
2012
A new method to control stochastic systems in the presence of input and state constraints is presented. The method exploits a… (More)
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Highly Cited
2011
Highly Cited
2011
MOTIVATION Several dynamic programming algorithms for predicting RNA structures with pseudoknots have been proposed that differ… (More)
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2010
2010
This paper provides a sparse learning algorithm for Support Vector Classification (SVC), called Sparse Support Vector… (More)
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2007
2007
In the rst part of this article, we have shown how time-dependent optimal control for partial di erential equations can be… (More)
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1988
1988
The application of Tikhonov's regularization method [Tikhonov & Arsenin (1977). Solution of Ill-Posed Problems. New York: Wiley… (More)
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