Matrix regularization

Known as: Regularization 
In the field of statistical learning theory, matrix regularization generalizes notions of vector regularization to cases where the object to be… (More)
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Topic mentions per year

1969-2018
020040060080019692018

Papers overview

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Highly Cited
2011
Highly Cited
2011
Although Recommender Systems have been comprehensively analyzed in the past decade, the study of social-based recommender systems… (More)
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Highly Cited
2007
Highly Cited
2007
In this paper, we study statistical inverse problems. We are interested in the case where the operator is not exactly known… (More)
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Highly Cited
2007
Highly Cited
2007
This paper considers regularizing a covariance matrix of p variables estimated from n observations, by hard thresholding. We show… (More)
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Highly Cited
2006
Highly Cited
2006
We propose a family of learning algorithms based on a new form f regularization that allows us to exploit the geometry of the… (More)
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Highly Cited
2005
Highly Cited
2005
Recent theoretical results describing the sum capacity when using multiple antennas to communicate with multiple users in a known… (More)
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Highly Cited
2003
Highly Cited
2003
We introduce a family of kernels on graphs based on the notion of regularization operators. This generalizes in a natural way the… (More)
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Highly Cited
1998
Highly Cited
1998
In this paper a correspondence is derived between regularization operators used in regularization networks and support vector… (More)
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Highly Cited
1995
Highly Cited
1995
We had previously shown that regularization principles lead to approximation schemes that are equivalent to networks with one… (More)
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Highly Cited
1995
Highly Cited
1995
It is well known that the addition of noise to the input data of a neural network during training can, in some circumstances… (More)
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Highly Cited
1986
Highly Cited
1986
Inverse problems, such as the reconstruction problems that arise in early vision, tend to be mathematically ill-posed. Through… (More)
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