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» Reinforcement Learning with Time
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147
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ANSS
2000
IEEE
15 years 8 months ago
Flow Control and Dynamic Load Balancing in Time Warp
We present, in this paper, an algorithm which integrates flow control and dynamic load balancing in Time Warp. The algorithm is intended for use in a distributed memory environme...
Myongsu Choe, Carl Tropper
ML
2000
ACM
185views Machine Learning» more  ML 2000»
15 years 3 months ago
A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty-Three Old and New Classification Algorithms
Twenty-two decision tree, nine statistical, and two neural network algorithms are compared on thirty-two datasets in terms of classification accuracy, training time, and (in the ca...
Tjen-Sien Lim, Wei-Yin Loh, Yu-Shan Shih
ICRA
2005
IEEE
118views Robotics» more  ICRA 2005»
15 years 9 months ago
Learning-Assisted Multi-Step Planning
— Probabilistic sampling-based motion planners are unable to detect when no feasible path exists. A common heuristic is to declare a query infeasible if a path is not found in a ...
Kris K. Hauser, Timothy Bretl, Jean-Claude Latombe
BC
2002
91views more  BC 2002»
15 years 4 months ago
Mathematical formulations of Hebbian learning
Several formulations of correlation-based Hebbian learning are reviewed. On the presynaptic side, activity is described either by a firing rate or by presynaptic spike arrival. The...
Wulfram Gerstner, Werner M. Kistler
124
Voted
CORR
2010
Springer
127views Education» more  CORR 2010»
15 years 2 months ago
Learning Networks of Stochastic Differential Equations
We consider linear models for stochastic dynamics. To any such model can be associated a network (namely a directed graph) describing which degrees of freedom interact under the d...
José Bento, Morteza Ibrahimi, Andrea Montan...