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ESANN
2006
15 years 8 months ago
Reducing policy degradation in neuro-dynamic programming
We focus on neuro-dynamic programming methods to learn state-action value functions and outline some of the inherent problems to be faced, when performing reinforcement learning in...
Thomas Gabel, Martin Riedmiller
ESANN
2001
15 years 7 months ago
Penalized least squares, model selection, convex hull classes and neural nets
We develop improved risk bounds for function estimation with models such as single hidden layer neural nets, using a penalized least squares criterion to select the size of the mod...
Gerald H. L. Cheang, Andrew R. Barron
DMTCS
2003
89views Mathematics» more  DMTCS 2003»
15 years 7 months ago
On the Monotonic Computability of Semi-computable Real Numbers
Let h : N → Q be a computable function. A real number x is h-monotonically computable (h-mc, for short) if there is a computable sequence (xs) of rational numbers which converges...
Xizhong Zheng, George Barmpalias
AMC
2010
86views more  AMC 2010»
15 years 6 months ago
BVMs for computing Sturm-Liouville symmetric potentials
The paper deals with the numerical solution of inverse Sturm-Liouville problems with unknown potential symmetric over the interval [0, ]. The proposed method is based on the use o...
Paolo Ghelardoni, Cecilia Magherini
FUIN
2006
95views more  FUIN 2006»
15 years 6 months ago
Bounds for Validation
In this paper we derive the bounds for Validation (known also as Hold-Out Estimate and Train-and-Test Method). We present the best possible bound in the case of 0-1 valued loss fun...
Wojciech Jaworski