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ICML
2004
IEEE
14 years 9 months ago
The Bayesian backfitting relevance vector machine
Traditional non-parametric statistical learning techniques are often computationally attractive, but lack the same generalization and model selection abilities as state-of-the-art...
Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal
ICML
2004
IEEE
14 years 9 months ago
Bayesian inference for transductive learning of kernel matrix using the Tanner-Wong data augmentation algorithm
In kernel methods, an interesting recent development seeks to learn a good kernel from empirical data automatically. In this paper, by regarding the transductive learning of the k...
Zhihua Zhang, Dit-Yan Yeung, James T. Kwok
PAMI
2006
147views more  PAMI 2006»
13 years 8 months ago
Bayesian Gaussian Process Classification with the EM-EP Algorithm
Gaussian process classifiers (GPCs) are Bayesian probabilistic kernel classifiers. In GPCs, the probability of belonging to a certain class at an input location is monotonically re...
Hyun-Chul Kim, Zoubin Ghahramani
ICPR
2008
IEEE
14 years 3 months ago
Adaptive semantic Bayesian framework for image attention
Image attention is the basic technique for many computer vision applications. In this paper, we propose an adaptive Bayesian framework to detect the image attention in color image...
Wei Zhang, Q. M. Jonathan Wu, Guanghui Wang
ICRA
2005
IEEE
116views Robotics» more  ICRA 2005»
14 years 2 months ago
Using Hierarchical EM to Extract Planes from 3D Range Scans
— Recently, the acquisition of three-dimensional maps has become more and more popular. This is motivated by the fact that robots act in the three-dimensional world and several t...
Rudolph Triebel, Wolfram Burgard, Frank Dellaert