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TSMC
2010
13 years 2 months ago
Probability Density Estimation With Tunable Kernels Using Orthogonal Forward Regression
A generalized or tunable-kernel model is proposed for probability density function estimation based on an orthogonal forward regression procedure. Each stage of the density estimat...
Sheng Chen, Xia Hong, Chris J. Harris
ACCV
2010
Springer
13 years 2 months ago
Latent Gaussian Mixture Regression for Human Pose Estimation
Discriminative approaches for human pose estimation model the functional mapping, or conditional distribution, between image features and 3D pose. Learning such multi-modal models ...
Yan Tian, Leonid Sigal, Hernán Badino, Fern...
ICASSP
2008
IEEE
14 years 2 months ago
Sequential experimental design for misspecified nonlinear models
In design of experiments for nonlinear regression model identification, the design criterion depends on the unknown parameters to be identified. Classical strategies consist in ...
H. ElAbiad, Laurent Le Brusquet, Marie-Eve Davoust
BMCBI
2011
13 years 2 months ago
Statistical learning techniques applied to epidemiology: a simulated case-control comparison study with logistic regression
Background: When investigating covariate interactions and group associations with standard regression analyses, the relationship between the response variable and exposure may be ...
John J. Heine, Walker H. Land Jr., Kathleen M. Ega...
IROS
2007
IEEE
168views Robotics» more  IROS 2007»
14 years 1 months ago
Improving humanoid locomotive performance with learnt approximated dynamics via Gaussian processes for regression
Abstract— We propose to improve the locomotive performance of humanoid robots by using approximated biped stepping and walking dynamics with reinforcement learning (RL). Although...
Jun Morimoto, Christopher G. Atkeson, Gen Endo, Go...