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» Nonlinear functional regression: a functional RKHS approach
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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...
ICCV
2009
IEEE
14 years 11 months ago
Time Series Prediction by Chaotic Modeling of Nonlinear Dynamical Systems
We use concepts from chaos theory in order to model nonlinear dynamical systems that exhibit deterministic behavior. Observed time series from such a system can be embedded into...
Arslan Basharat, Mubarak Shah
ICML
2006
IEEE
14 years 7 months ago
Regression with the optimised combination technique
We consider the sparse grid combination technique for regression, which we regard as a problem of function reconstruction in some given function space. We use a regularised least ...
Jochen Garcke
GECCO
2007
Springer
175views Optimization» more  GECCO 2007»
14 years 26 days ago
An evolutionary multiobjective approach to design highly non-linear Boolean functions
The proliferation of all kinds of devices with different security requirements and constraints, and the arms-race nature of the security problem are increasingly demanding the de...
Hernán E. Aguirre, Hiroyuki Okazaki, Yasush...
ICML
2007
IEEE
14 years 7 months ago
Regression on manifolds using kernel dimension reduction
We study the problem of discovering a manifold that best preserves information relevant to a nonlinear regression. Solving this problem involves extending and uniting two threads ...
Jens Nilsson, Fei Sha, Michael I. Jordan