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» Using Learning for Approximation in Stochastic Processes
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ECML
2005
Springer
15 years 10 months ago
Natural Actor-Critic
This paper investigates a novel model-free reinforcement learning architecture, the Natural Actor-Critic. The actor updates are based on stochastic policy gradients employing Amari...
Jan Peters, Sethu Vijayakumar, Stefan Schaal
ICON
2007
IEEE
15 years 10 months ago
An Approximate Analysis of the Balance among Performance, Utilization and Power Estimation of Server Systems by Use of the Batch
- In this paper we analyze the performance, utilization, and power estimation of server systems by both adopting the batch service and adjusting the batch size. In addition to redu...
Ying-Wen Bai, Yung-Sen Cheng, Cheng-Hung Tsai
EMSOFT
2007
Springer
15 years 8 months ago
A unified practical approach to stochastic DVS scheduling
This paper deals with energy-aware real-time system scheduling using dynamic voltage scaling (DVS) for energy-constrained embedded systems that execute variable and unpredictable ...
Ruibin Xu, Rami G. Melhem, Daniel Mossé
COR
2008
122views more  COR 2008»
15 years 4 months ago
First steps to the runtime complexity analysis of ant colony optimization
: The paper presents results on the runtime complexity of two ant colony optimization (ACO) algorithms: Ant System, the oldest ACO variant, and GBAS, the first ACO variant for whic...
Walter J. Gutjahr
EMNLP
2010
15 years 2 months ago
Turbo Parsers: Dependency Parsing by Approximate Variational Inference
We present a unified view of two state-of-theart non-projective dependency parsers, both approximate: the loopy belief propagation parser of Smith and Eisner (2008) and the relaxe...
André F. T. Martins, Noah A. Smith, Eric P....