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» Relational temporal difference learning
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WCE
2007
13 years 11 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
13 years 11 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
13 years 7 months 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»
13 years 9 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
BMCBI
2006
148views more  BMCBI 2006»
13 years 10 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 ...