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» Relational temporal difference learning
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WCE
2007
15 years 3 months ago
Modelling of Reciprocal Transducer System Accounting for Nonlinear Constitutive Relations
—The dynamics of reciprocal transducer systems is modelled accounting for a nonlinear constitutive relation between the electric displacement and the electric field as reported ...
Linxiang X. Wang, Morten Willatzen, Roderick V. N....
FLAIRS
2003
15 years 3 months ago
Learning Opening Strategy in the Game of Go
In this paper, we present an experimental methodology and results for a machine learning approach to learning opening strategy in the game of Go, a game for which the best compute...
Timothy Huang, Graeme Connell, Bryan McQuade
ICMLA
2009
15 years 2 days ago
Learning Parameters for Relational Probabilistic Models with Noisy-Or Combining Rule
Languages that combine predicate logic with probabilities are needed to succinctly represent knowledge in many real-world domains. We consider a formalism based on universally qua...
Sriraam Natarajan, Prasad Tadepalli, Gautam Kunapu...
NN
1998
Springer
108views Neural Networks» more  NN 1998»
15 years 2 months ago
How embedded memory in recurrent neural network architectures helps learning long-term temporal dependencies
Learning long-term temporal dependencies with recurrent neural networks can be a difficult problem. It has recently been shown that a class of recurrent neural networks called NA...
Tsungnan Lin, Bill G. Horne, C. Lee Giles
138
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BMCBI
2006
148views more  BMCBI 2006»
15 years 2 months ago
Exploiting the full power of temporal gene expression profiling through a new statistical test: Application to the analysis of m
Background: The identification of biologically interesting genes in a temporal expression profiling dataset is challenging and complicated by high levels of experimental noise. Mo...
Veronica Vinciotti, Xiaohui Liu, Rolf Turk, Emile ...