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Manifold regularization

In machine learning, Manifold regularization is a technique for using the shape of a dataset to constrain the functions that should be learned on… 
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2012
2012
Domain adaptation algorithms that handle shifts in the distribution between training and testing data are receiving much… 
2012
2012
A holistic or appearance-based eigenfeature regularization methodology based on a three-parameter eigenmodel improves computer… 
2009
2009
In this paper we consider nonlinear ill-posed problems with piecewise constant or strongly varying solutions. A class of… 
2008
2008
Head pose estimation has been an integral problem in the study of face recognition systems and human-computer interfaces, as part… 
1997
1997
Witt's theorem on the extension of H-isometries to H-unitary matrices with respect to the scalar product generated by a self… 
Highly Cited
1994
Highly Cited
1994
Concepts of well-posedness stabilizing techniques for ill-posed problems Tikhonov's principle prox-regularization methods of… 
1991
1991
A method based on an augmented Lagrangian formulation is developed which allows coefficients in an elliptic differential equation…