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» On regularization algorithms in learning theory
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COMPGEOM
2003
ACM
15 years 9 months ago
Updating and constructing constrained delaunay and constrained regular triangulations by flips
I discuss algorithms based on bistellar flips for inserting and deleting constraining (d − 1)-facets in d-dimensional constrained Delaunay triangulations (CDTs) and weighted CD...
Jonathan Richard Shewchuk
JMLR
2010
82views more  JMLR 2010»
14 years 11 months ago
On Spectral Learning
In this paper, we study the problem of learning a matrix W from a set of linear measurements. Our formulation consists in solving an optimization problem which involves regulariza...
Andreas Argyriou, Charles A. Micchelli, Massimilia...
ICML
2010
IEEE
15 years 5 months ago
A Fast Augmented Lagrangian Algorithm for Learning Low-Rank Matrices
We propose a general and efficient algorithm for learning low-rank matrices. The proposed algorithm converges super-linearly and can keep the matrix to be learned in a compact fac...
Ryota Tomioka, Taiji Suzuki, Masashi Sugiyama, His...
WSDM
2012
ACM
259views Data Mining» more  WSDM 2012»
14 years 1 days ago
Learning recommender systems with adaptive regularization
Many factorization models like matrix or tensor factorization have been proposed for the important application of recommender systems. The success of such factorization models dep...
Steffen Rendle
ICIP
2007
IEEE
15 years 10 months ago
Classification by Cheeger Constant Regularization
This paper develops a classification algorithm in the framework of spectral graph theory where the underlying manifold of a high dimensional data set is described by a graph. The...
Hsun-Hsien Chang, José M. F. Moura