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» Missing Data Estimation Using Polynomial Kernels
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ICML
2004
IEEE
16 years 1 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
AMDO
2008
Springer
15 years 2 months ago
Predicting Missing Markers to Drive Real-Time Centre of Rotation Estimation
This paper addresses the problem of real-time location of the joints or centres of rotation (CoR) of human skeletons in the presence of missing data. The data is assumed to be 3d m...
Andreas Aristidou, Jonathan Cameron, Joan Lasenby
102
Voted
CORR
2006
Springer
96views Education» more  CORR 2006»
15 years 14 days ago
How accurate are the time delay estimates in gravitational lensing?
We present a novel approach to estimate the time delay between light curves of multiple images in a gravitationally lensed system, based on Kernel methods in the context of machine...
Juan C. Cuevas-Tello, Peter Tino, Somak Raychaudhu...
105
Voted
IBPRIA
2007
Springer
15 years 6 months ago
Motion Segmentation from Feature Trajectories with Missing Data
Abstract. This paper presents a novel approach for motion segmentation from feature trajectories with missing data. It consists of two stages. In the first stage, missing data are...
Carme Julià, Angel Domingo Sappa, Felipe Lu...
99
Voted
IVC
2006
133views more  IVC 2006»
15 years 12 days ago
A subspace method for projective reconstruction from multiple images with missing data
In this paper, we consider the problem of projective reconstruction based on the subspace method. Unlike existing subspace methods which require that all the points are visible in...
W. K. Tang, Y. S. Hung