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ICML
1996
IEEE
15 years 2 months ago
A Convergent Reinforcement Learning Algorithm in the Continuous Case: The Finite-Element Reinforcement Learning
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
Rémi Munos
IBPRIA
2009
Springer
15 years 2 months ago
Inference and Learning for Active Sensing, Experimental Design and Control
In this paper we argue that maximum expected utility is a suitable framework for modeling a broad range of decision problems arising in pattern recognition and related fields. Exa...
Hendrik Kück, Matthew Hoffman, Arnaud Doucet,...
INFOCOM
2008
IEEE
15 years 4 months ago
A Distributed Optimization Algorithm for Multi-Hop Cognitive Radio Networks
Cognitive radio (CR) is a revolution in radio technology and is viewed as an enabling technology for dynamic spectrum access. This paper investigates how to design distributed alg...
Yi Shi, Y. Thomas Hou
WCE
2007
14 years 11 months ago
Neural Networks for Optimal Control of Aircraft Landing Systems
Abstract—In this work we present a variational formulation for a multilayer perceptron neural network. With this formulation any learning task for the neural network is defined ...
Kevin Lau, Roberto Lopez, Eugenio Oñate
NIPS
2001
14 years 11 months ago
On the Convergence of Leveraging
We give an unified convergence analysis of ensemble learning methods including e.g. AdaBoost, Logistic Regression and the Least-SquareBoost algorithm for regression. These methods...
Gunnar Rätsch, Sebastian Mika, Manfred K. War...