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PKDD
2010
Springer
179views Data Mining» more  PKDD 2010»
13 years 5 months ago
Gaussian Processes for Sample Efficient Reinforcement Learning with RMAX-Like Exploration
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
Tobias Jung, Peter Stone
ICML
2010
IEEE
13 years 8 months ago
Continuous-Time Belief Propagation
Many temporal processes can be naturally modeled as a stochastic system that evolves continuously over time. The representation language of continuous-time Bayesian networks allow...
Tal El-Hay, Ido Cohn, Nir Friedman, Raz Kupferman
ICSNC
2007
IEEE
14 years 2 months ago
Movement Prediction Using Bayesian Learning for Neural Networks
Nowadays, path prediction is being extensively examined for use in the context of mobile and wireless computing towards more efficient network resource management schemes. Path pr...
Sherif Akoush, Ahmed Sameh
FLAIRS
2003
13 years 9 months ago
Using Bayesian Networks for Cleansing Trauma Data
Medical data is unique due to its large volume, heterogeneity and complexity. This necessitates costly active participation of medical domain experts in the task of cleansing medi...
Prashant Doshi, Lloyd Greenwald, John R. Clarke
SYNTHESE
2008
130views more  SYNTHESE 2008»
13 years 7 months ago
Appropriateness measures: an uncertainty model for vague concepts
Abstract We argue that in the decision making process required for selecting assertible vague descriptions of an object, it is practical that communicating agents adopt an epistemi...
Jonathan Lawry