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» Scale-Time Kernels and Models
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CVPR
2008
IEEE
14 years 10 months ago
Parameterized Kernel Principal Component Analysis: Theory and applications to supervised and unsupervised image alignment
Parameterized Appearance Models (PAMs) (e.g. eigentracking, active appearance models, morphable models) use Principal Component Analysis (PCA) to model the shape and appearance of...
Fernando De la Torre, Minh Hoai Nguyen
ACST
2006
13 years 10 months ago
Domain decomposition by radial basis functions for time dependent partial differential equations
In the last years, there has been an increased investigation of efficient algorithms to solve problems of great scale. The main restriction of the traditional methods, like finite...
José Antonio Muñoz-Gómez, Ped...
JMLR
2011
142views more  JMLR 2011»
13 years 3 months ago
Causal Search in Structural Vector Autoregressive Models
This paper reviews a class of methods to perform causal inference in the framework of a structural vector autoregressive model. We consider three different settings. In the first ...
Alessio Moneta, Nadine Chlass, Doris Entner, Patri...
ECML
2004
Springer
14 years 2 months ago
Fisher Kernels for Logical Sequences
One approach to improve the accuracy of classifications based on generative models is to combine them with successful discriminative algorithms. Fisher kernels were developed to c...
Kristian Kersting, Thomas Gärtner
PKDD
2009
Springer
184views Data Mining» more  PKDD 2009»
14 years 3 months ago
Learning Preferences with Hidden Common Cause Relations
Abstract. Gaussian processes have successfully been used to learn preferences among entities as they provide nonparametric Bayesian approaches for model selection and probabilistic...
Kristian Kersting, Zhao Xu