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NIPS
2008
13 years 8 months ago
Non-stationary dynamic Bayesian networks
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Joshua W. Robinson, Alexander J. Hartemink
AAAI
2010
13 years 8 months ago
Cost-Sensitive Semi-Supervised Support Vector Machine
In this paper, we study cost-sensitive semi-supervised learning where many of the training examples are unlabeled and different misclassification errors are associated with unequa...
Yu-Feng Li, James T. Kwok, Zhi-Hua Zhou
ICIP
2006
IEEE
14 years 9 months ago
Support Vector Machines for Camera Calibration Problem
This paper presents a statistical learning-based solution to the camera calibration problem in which the Support Vector Machines (SVM) are used for the estimation of the projectio...
Refaat M. Mohamed, Abdelrehim H. Ahmed, Ahmed Eid,...
CVPR
2007
IEEE
14 years 9 months ago
A Multi-Scale Tikhonov Regularization Scheme for Implicit Surface Modelling
Kernel machines have recently been considered as a promising solution for implicit surface modelling. A key challenge of machine learning solutions is how to fit implicit shape mo...
Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu
TVCG
1998
129views more  TVCG 1998»
13 years 7 months ago
Splatting Errors and Antialiasing
—This paper describes three new results for volume rendering algorithms utilizing splatting. First, an antialiasing extension to the basic splatting algorithm is introduced that ...
Klaus Mueller, Torsten Möller, J. Edward Swan...