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SDM
2004
SIAM
218views Data Mining» more  SDM 2004»
13 years 9 months ago
Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
Ashok N. Srivastava
IJON
2007
118views more  IJON 2007»
13 years 7 months ago
CATS benchmark time series prediction by Kalman smoother with cross-validated noise density
This article presents the winning solution to the CATS time series prediction competition. The solution is based on classical optimal linear estimation theory. The proposed method...
Simo Särkkä, Aki Vehtari, Jouko Lampinen
ICIP
2001
IEEE
14 years 9 months ago
Compression color space estimation of JPEG images using lattice basis reduction
Given a color image that was quantized in some hidden color space (termed compression color space) during previous JPEG compression, we aim to estimate this unknown compression co...
Ramesh Neelamani, Ricardo L. de Queiroz, Richard G...
ICPR
2006
IEEE
14 years 8 months ago
Domain Based LDA and QDA
We propose an alternative to probability density classifiers based on normal distributions LDA and QDA. Instead of estimating covariance matrices using the standard maximum likeli...
David M. J. Tax, Piotr Juszczak, Robert P. W. Duin...
TNN
2008
142views more  TNN 2008»
13 years 7 months ago
Multiclass Posterior Probability Support Vector Machines
Abstract--Tao et al. have recently proposed the posterior probability support vector machine (PPSVM) which uses soft labels derived from estimated posterior probabilities to be mor...
Mehmet Gönen, Ayse Gönül Tanugur, E...