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» Gaussian Processes in Reinforcement Learning
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ICML
2001
IEEE
16 years 20 days ago
Off-Policy Temporal Difference Learning with Function Approximation
We introduce the first algorithm for off-policy temporal-difference learning that is stable with linear function approximation. Off-policy learning is of interest because it forms...
Doina Precup, Richard S. Sutton, Sanjoy Dasgupta
ICTAI
2005
IEEE
15 years 5 months ago
Latent Process Model for Manifold Learning
In this paper, we propose a novel stochastic framework for unsupervised manifold learning. The latent variables are introduced, and the latent processes are assumed to characteriz...
Gang Wang, Weifeng Su, Xiangye Xiao, Frederick H. ...
CORR
2010
Springer
134views Education» more  CORR 2010»
14 years 12 months ago
Large Margin Multiclass Gaussian Classification with Differential Privacy
As increasing amounts of sensitive personal information is aggregated into data repositories, it has become important to develop mechanisms for processing the data without revealin...
Manas A. Pathak, Bhiksha Raj
AAAI
1997
15 years 1 months ago
Machine Learning for Intelligent Systems
Recent research in machine learning has focused on supervised induction for simple classi cation and reinforcement learning for simple reactive behaviors. In the process, the eld ...
Pat Langley
HIS
2008
15 years 1 months ago
New Crossover Operator for Evolutionary Rule Discovery in XCS
XCS is a learning classifier system that combines a reinforcement learning scheme with evolutionary algorithms to evolve rule sets on-line by means of the interaction with an envi...
Sergio Morales-Ortigosa, Albert Orriols-Puig, Este...