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ESANN
2008
13 years 10 months ago
Approximation of Gaussian process regression models after training
The evaluation of a standard Gaussian process regression model takes time linear in the number of training data points. In this paper, the models are approximated in the feature sp...
Thorsten Suttorp, Christian Igel
DAGSTUHL
2004
13 years 10 months ago
Numerical Approximation of Parabolic Stochastic Partial Differential Equations
The topic of the talk were the time approximation of quasi linear stochastic partial differential equations of parabolic type. The framework were in the setting of stochastic evolu...
Erika Hausenblas
ICML
2010
IEEE
13 years 10 months ago
Toward Off-Policy Learning Control with Function Approximation
We present the first temporal-difference learning algorithm for off-policy control with unrestricted linear function approximation whose per-time-step complexity is linear in the ...
Hamid Reza Maei, Csaba Szepesvári, Shalabh ...
JCP
2007
118views more  JCP 2007»
13 years 9 months ago
Dynamic Nonuniform Data Approximation in Databases with Haar Wavelet
Abstract— Data synopsis is a lossy compressed representation of data stored into databases that helps the query optimizer to speed up the query process, e.g. time to retrieve the...
Su Chen, Antonio Nucci
TROB
2010
129views more  TROB 2010»
13 years 7 months ago
A Probabilistic Particle-Control Approximation of Chance-Constrained Stochastic Predictive Control
—Robotic systems need to be able to plan control actions that are robust to the inherent uncertainty in the real world. This uncertainty arises due to uncertain state estimation,...
Lars Blackmore, Masahiro Ono, Askar Bektassov, Bri...