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289views
12 years 5 months ago
An Analysis of Finite Volume, Finite Element, and Finite Difference Methods Using Some Concepts from Algebraic Topology
In this paper we apply the ideas of algebraic topology to the analysis of the finite volume and finite element methods, illuminating the similarity between the discretization str...
Claudio Mattiussi
ICONIP
2009
13 years 5 months ago
Learning Gaussian Process Models from Uncertain Data
It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...
Patrick Dallaire, Camille Besse, Brahim Chaib-draa
BMCBI
2005
153views more  BMCBI 2005»
13 years 7 months ago
Learning Statistical Models for Annotating Proteins with Function Information using Biomedical Text
Background: The BioCreative text mining evaluation investigated the application of text mining methods to the task of automatically extracting information from text in biomedical ...
Soumya Ray, Mark Craven
CORR
2007
Springer
112views Education» more  CORR 2007»
13 years 7 months ago
Learning from compressed observations
— The problem of statistical learning is to construct a predictor of a random variable Y as a function of a related random variable X on the basis of an i.i.d. training sample fr...
Maxim Raginsky
ICML
2004
IEEE
14 years 8 months ago
Learning with non-positive kernels
In this paper we show that many kernel methods can be adapted to deal with indefinite kernels, that is, kernels which are not positive semidefinite. They do not satisfy Mercer...
Alexander J. Smola, Cheng Soon Ong, Stéphan...