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AAAI
1997
13 years 9 months ago
Effective Bayesian Inference for Stochastic Programs
In this paper, we propose a stochastic version of a general purpose functional programming language as a method of modeling stochastic processes. The language contains random choi...
Daphne Koller, David A. McAllester, Avi Pfeffer
CJ
2008
97views more  CJ 2008»
13 years 8 months ago
Three Kinds of Probabilistic Induction: Universal Distributions and Convergence Theorems
We will describe three kinds of probabilistic induction problems, and give general solutions for each , with associated convergence theorems that show they tend to give good proba...
Ray J. Solomonoff
IJON
2008
88views more  IJON 2008»
13 years 7 months ago
Neural network construction and training using grammatical evolution
The term neural network evolution usually refers to network topology evolution leaving the network's parameters to be trained using conventional algorithms. In this paper we ...
Ioannis G. Tsoulos, Dimitris Gavrilis, Euripidis G...
IS
2008
13 years 7 months ago
Efficient memory representation of XML document trees
Implementations that load XML documents and give access to them via, e.g., the DOM, suffer from huge memory demands: the space needed to load an XML document is usually many times...
Giorgio Busatto, Markus Lohrey, Sebastian Maneth
AMAI
1998
Springer
13 years 7 months ago
Generalization and Specialization Strategies for Learning r.e. Languages
Overgeneralization is a major issue in the identification of grammars for formal languages from positive data. Different formulations of generalization and specialization strate...
Sanjay Jain, Arun Sharma