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ICML
1995
IEEE
16 years 7 months ago
Stable Function Approximation in Dynamic Programming
The success ofreinforcement learninginpractical problems depends on the ability to combine function approximation with temporal di erence methods such as value iteration. Experime...
Geoffrey J. Gordon
ICANN
2007
Springer
15 years 10 months ago
Resilient Approximation of Kernel Classifiers
Abstract. Trained support vector machines (SVMs) have a slow runtime classification speed if the classification problem is noisy and the sample data set is large. Approximating the...
Thorsten Suttorp, Christian Igel
AUTOMATICA
2006
111views more  AUTOMATICA 2006»
15 years 6 months ago
The minimal disturbance invariant set: Outer approximations via its partial sums
This paper is concerned with outer approximations of the minimal disturbance invariant set (MDIS) of a discrete-time linear system with an additive set-bounded disturbance. The k-...
Chong Jin Ong, Elmer G. Gilbert
MCS
2008
Springer
15 years 5 months ago
Dynamical low-rank approximation: applications and numerical experiments
Dynamical low-rank approximation is a differential-equation based approach to efficiently computing low-rank approximations to time-dependent large data matrices or to solutions o...
Achim Nonnenmacher, Christian Lubich
174
Voted
SIAMMAX
2010
134views more  SIAMMAX 2010»
15 years 26 days ago
Dynamical Tensor Approximation
For the approximation of time-dependent data tensors and of solutions to tensor differential equations by tensors of low Tucker rank, we study a computational approach that can be ...
Othmar Koch, Christian Lubich