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ICML
2005
IEEE
15 years 10 months ago
Predictive low-rank decomposition for kernel methods
Low-rank matrix decompositions are essential tools in the application of kernel methods to large-scale learning problems. These decompositions have generally been treated as black...
Francis R. Bach, Michael I. Jordan
COMPGEOM
2004
ACM
15 years 3 months ago
Approximate convex decomposition of polygons
We propose a strategy to decompose a polygon, containing zero or more holes, into “approximately convex” pieces. For many applications, the approximately convex components of ...
Jyh-Ming Lien, Nancy M. Amato
CORR
2006
Springer
117views Education» more  CORR 2006»
14 years 9 months ago
Explicit factors of some iterated resultants and discriminants
In this paper, the result of applying iterative univariate resultant constructions to multivariate polynomials is analyzed. We consider the input polynomials as generic polynomials...
Laurent Busé, Bernard Mourrain
AAECC
2004
Springer
63views Algorithms» more  AAECC 2004»
14 years 9 months ago
Computation of the Decomposition Group of a Triangular Ideal
Abstract. This article describes two algorithms in order to search decomposition groups of ideals of polynomials with coefficients in a perfect field when those ideals are generate...
I. Abdeljaouad-Tej, Sébastien Orange, Gu&ea...
JUCS
2006
112views more  JUCS 2006»
14 years 9 months ago
Construction of Wavelets and Applications
: A sequence of increasing translation invariant subspaces can be defined by the Haar-system (or generally by wavelets). The orthogonal projection to the subspaces generates a deco...
Ildikó László, Ferenc Schipp,...