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» Learning Gaussian Process Models from Uncertain Data
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ICML
2005
IEEE
14 years 7 months ago
Reinforcement learning with Gaussian processes
Gaussian Process Temporal Difference (GPTD) learning offers a Bayesian solution to the policy evaluation problem of reinforcement learning. In this paper we extend the GPTD framew...
Yaakov Engel, Shie Mannor, Ron Meir
ESSMAC
2003
Springer
13 years 12 months ago
Self-tuning Control of Non-linear Systems Using Gaussian Process Prior Models
Gaussian Process prior models, as used in Bayesian non-parametric statistical models methodology are applied to implement a nonlinear adaptive control law. The expected value of a...
Daniel Sbarbaro, Roderick Murray-Smith
ICPR
2010
IEEE
14 years 1 months ago
Gait Learning-Based Regenerative Model: A Level Set Approach
We propose a learning method for gait synthesis from a sequence of shapes(frames) with the ability to extrapolate to novel data. It involves the application of PCA, first to redu...
Muayed Sattar Al-Huseiny, Sasan Mahmoodi, Mark Nix...
ICML
2003
IEEE
14 years 7 months ago
Robust Induction of Process Models from Time-Series Data
Pat Langley, Dileep George, Stephen D. Bay, Kazumi...
FLAIRS
2007
13 years 9 months ago
Learning Uncertain Rules with CONDORCKD
CONDORCKD is a system implementing a novel approach to discovering knowledge from data. It addresses the issue of relevance of the learned rules by algebraic means and explicitly ...
Jens Fisseler, Gabriele Kern-Isberner, Christoph B...