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» Complexity Dimensions and Learnability
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COMPUTING
2006
119views more  COMPUTING 2006»
14 years 12 months ago
Sparse Grids, Adaptivity, and Symmetry
Sparse grid methods represent a powerful and efficient technique for the representation and approximation of functions and particularly the solutions of partial differential equat...
Harry Yserentant
COMGEO
2007
ACM
14 years 12 months ago
An incremental algorithm for reconstruction of surfaces of arbitrary codimension
A new algorithm is presented for surface reconstruction from unorganized points. Unlike many previous algorithms, this algorithm does not select a subcomplex of the Delaunay Trian...
Daniel Freedman
JMLR
2008
133views more  JMLR 2008»
14 years 11 months ago
Algorithms for Sparse Linear Classifiers in the Massive Data Setting
Classifiers favoring sparse solutions, such as support vector machines, relevance vector machines, LASSO-regression based classifiers, etc., provide competitive methods for classi...
Suhrid Balakrishnan, David Madigan
JMIV
2006
94views more  JMIV 2006»
14 years 11 months ago
Geodesic Shooting for Computational Anatomy
Studying large deformations with a Riemannian approach has been an efficient point of view to generate metrics between deformable objects, and to provide accurate, non ambiguous an...
Michael I. Miller, Alain Trouvé, Laurent Yo...
MP
2008
129views more  MP 2008»
14 years 11 months ago
Corrector-predictor methods for monotone linear complementarity problems in a wide neighborhood of the central path
Abstract. Two corrector-predictor interior point algorithms are proposed for solving monotone linear complementarity problems. The algorithms produce a sequence of iterates in the ...
Florian A. Potra