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» Using Problems to Learn Service-Oriented Computing
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ICPR
2006
IEEE
16 years 7 months ago
Control Double Inverted Pendulum by Reinforcement Learning with Double CMAC Network
To accelerate the learning of reinforcement learning, many types of function approximation are used to represent state value. However function approximation reduces the accuracy o...
Siwei Luo, Yu Zheng, Ziang Lv
AIMSA
2008
Springer
16 years 20 days ago
Incorporating Learning in Grid-Based Randomized SAT Solving
Abstract. Computational Grids provide a widely distributed computing environment suitable for randomized SAT solving. This paper develops techniques for incorporating learning, kno...
Antti Eero Johannes Hyvärinen, Tommi A. Juntt...
AIIA
2007
Springer
15 years 8 months ago
Tonal Harmony Analysis: A Supervised Sequential Learning Approach
We have recently presented CarpeDiem, an algorithm that can be used for speeding up the evaluation of Supervised Sequential Learning (SSL) classifiers. CarpeDiem provides impress...
Daniele P. Radicioni, Roberto Esposito
PR
2011
14 years 9 months ago
A survey of multilinear subspace learning for tensor data
Increasingly large amount of multidimensional data are being generated on a daily basis in many applications. This leads to a strong demand for learning algorithms to extract usef...
Haiping Lu, Konstantinos N. Plataniotis, Anastasio...
ECCV
2008
Springer
15 years 8 months ago
Vision-Based Multiple Interacting Targets Tracking via On-Line Supervised Learning
Abstract. Successful multi-target tracking requires locating the targets and labeling their identities. This mission becomes significantly more challenging when many targets freque...
Xuan Song, Jinshi Cui, Hongbin Zha, Huijing Zhao