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JMLR
2006
79views more  JMLR 2006»
13 years 7 months ago
Universal Kernels
In this paper we investigate conditions on the features of a continuous kernel so that it may approximate an arbitrary continuous target function uniformly on any compact subset o...
Charles A. Micchelli, Yuesheng Xu, Haizhang Zhang
ICML
2007
IEEE
14 years 8 months ago
Constructing basis functions from directed graphs for value function approximation
Basis functions derived from an undirected graph connecting nearby samples from a Markov decision process (MDP) have proven useful for approximating value functions. The success o...
Jeffrey Johns, Sridhar Mahadevan
AAAI
2006
13 years 8 months ago
Learning Representation and Control in Continuous Markov Decision Processes
This paper presents a novel framework for simultaneously learning representation and control in continuous Markov decision processes. Our approach builds on the framework of proto...
Sridhar Mahadevan, Mauro Maggioni, Kimberly Fergus...
ECML
2006
Springer
13 years 11 months ago
Task-Driven Discretization of the Joint Space of Visual Percepts and Continuous Actions
We target the problem of closed-loop learning of control policies that map visual percepts to continuous actions. Our algorithm, called Reinforcement Learning of Joint Classes (RLJ...
Sébastien Jodogne, Justus H. Piater
ESA
2010
Springer
246views Algorithms» more  ESA 2010»
13 years 8 months ago
Estimating the Average of a Lipschitz-Continuous Function from One Sample
We study the problem of estimating the average of a Lipschitz continuous function f defined over a metric space, by querying f at only a single point. More specifically, we explore...
Abhimanyu Das, David Kempe