311 search results - page 38 / 63 » Learning first-order probabilistic models with combining rul... |
113
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ICMI
2010
Springer
14 years 9 months ago
2010
Springer
Traditionally listener response prediction models are learned from pre-recorded dyadic interactions. Because of individual differences in behavior, these recordings do not capture...
126
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CORR
2011
Springer
14 years 3 months ago
2011
Springer
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. de nite clause programs containing probabilistic facts with a ...
WSC
2008
15 years 2 months ago
2008
Reinforcement Learning (RL) is a simulation-based technique useful in solving Markov decision processes if their transition probabilities are not easily obtainable or if the probl...
101
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RSS
2007
15 years 1 months ago
2007
— In probabilistic mobile robotics, the development of measurement models plays a crucial role as it directly influences the efficiency and the robustness of the robot’s perf...
ACL
2008
15 years 1 months ago
2008
Parse-tree paths are commonly used to incorporate information from syntactic parses into NLP systems. These systems typically treat the paths as atomic (or nearly atomic) features...