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ECSQARU
2009
Springer
16 years 1 months ago
Maximum Likelihood Learning of Conditional MTE Distributions
We describe a procedure for inducing conditional densities within the mixtures of truncated exponentials (MTE) framework. We analyse possible conditional MTE specifications and pr...
Helge Langseth, Thomas D. Nielsen, Rafael Rum&iacu...
DEXA
1998
Springer
152views Database» more  DEXA 1998»
15 years 11 months ago
Facilitating Virtual Representation of CAD Data Through A Learning Based Approach to Conceptual Database Evolution Employing Dir
This paper presents a framework for a learning based approach to dynamically evolve the conceptual structure of a database in order to facilitate virtual representation of data in ...
Awais Rashid, Peter Sawyer
KDD
1994
ACM
123views Data Mining» more  KDD 1994»
15 years 11 months ago
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data
We describe scoring metrics for learning Bayesian networks from a combination of user knowledge and statistical data. We identify two important properties of metrics, which we cal...
David Heckerman, Dan Geiger, David Maxwell Chicker...
ICAI
2004
15 years 8 months ago
Mixed-Initiative Ontology Learning
This paper presents a mixed-initiative assistant that supports a subject matter expert to extend the ontology of a learning agent, in order to express the subtle distinctions he ma...
Cristina Boicu, Gheorghe Tecuci
ATAL
2010
Springer
15 years 8 months ago
Basis function construction for hierarchical reinforcement learning
This paper introduces an approach to automatic basis function construction for Hierarchical Reinforcement Learning (HRL) tasks. We describe some considerations that arise when con...
Sarah Osentoski, Sridhar Mahadevan