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» Heteroscedastic Gaussian process regression
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115
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ICCV
2007
IEEE
16 years 1 months ago
The Joint Manifold Model for Semi-supervised Multi-valued Regression
Many computer vision tasks may be expressed as the problem of learning a mapping between image space and a parameter space. For example, in human body pose estimation, recent rese...
Ramanan Navaratnam, Andrew W. Fitzgibbon, Roberto ...
ICASSP
2010
IEEE
14 years 12 months ago
A novel estimation of feature-space MLLR for full-covariance models
In this paper we present a novel approach for estimating featurespace maximum likelihood linear regression (fMLLR) transforms for full-covariance Gaussian models by directly maxim...
Arnab Ghoshal, Daniel Povey, Mohit Agarwal, Pinar ...
ICRA
2008
IEEE
169views Robotics» more  ICRA 2008»
15 years 6 months ago
Sparse incremental learning for interactive robot control policy estimation
— We are interested in transferring control policies for arbitrary tasks from a human to a robot. Using interactive demonstration via teloperation as our transfer scenario, we ca...
Daniel H. Grollman, Odest Chadwicke Jenkins
89
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ESANN
2008
15 years 1 months ago
Learning Inverse Dynamics: a Comparison
While it is well-known that model can enhance the control performance in terms of precision or energy efficiency, the practical application has often been limited by the complexiti...
Duy Nguyen-Tuong, Jan Peters, Matthias Seeger, Ber...
102
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JMLR
2011
148views more  JMLR 2011»
14 years 6 months ago
Bayesian Generalized Kernel Mixed Models
We propose a fully Bayesian methodology for generalized kernel mixed models (GKMMs), which are extensions of generalized linear mixed models in the feature space induced by a repr...
Zhihua Zhang, Guang Dai, Michael I. Jordan