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119
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COLT
2000
Springer
15 years 9 months ago
Estimation and Approximation Bounds for Gradient-Based Reinforcement Learning
We model reinforcement learning as the problem of learning to control a Partially Observable Markov Decision Process (  ¢¡¤£¦¥§  ), and focus on gradient ascent approache...
Peter L. Bartlett, Jonathan Baxter
ISBI
2004
IEEE
16 years 5 months ago
A Fast Fully 4D Incremental Gradient Reconstruction Algorithm for List Mode PET Data
We present a fully four-dimensional, globally convergent, incremental gradient algorithm to estimate the continuous-time tracer density from list mode positron emission tomography...
Quanzheng Li, Evren Asma, Richard M. Leahy
ICASSP
2009
IEEE
15 years 11 months ago
Testing fractal connectivity in multivariate long memory processes
Within the framework of long memory multivariate processes, fractal connectivity is a particular model, in which the low frequencies (coarse scales) of the interspectrum of each p...
Herwig Wendt, Antoine Scherrer, Patrice Abry, Soph...
CEC
2009
IEEE
15 years 9 months ago
Memory-enhanced Evolutionary Robotics: The Echo State Network Approach
— Interested in Evolutionary Robotics, this paper focuses on the acquisition and exploitation of memory skills. The targeted task is a well-studied benchmark problem, the Tolman ...
Cédric Hartland, Nicolas Bredeche, Mich&egr...
191
Voted
CP
2006
Springer
15 years 8 months ago
Compiling Constraint Networks into AND/OR Multi-valued Decision Diagrams (AOMDDs)
Abstract. Inspired by AND/OR search spaces for graphical models recently introduced, we propose to augment Ordered Decision Diagrams with AND nodes, in order to capture function de...
Robert Mateescu, Rina Dechter