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ICML
2009
IEEE
16 years 5 months ago
Learning structurally consistent undirected probabilistic graphical models
In many real-world domains, undirected graphical models such as Markov random fields provide a more natural representation of the dependency structure than directed graphical mode...
Sushmita Roy, Terran Lane, Margaret Werner-Washbur...
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CEAS
2006
Springer
15 years 8 months ago
Learning at Low False Positive Rates
Most spam filters are configured for use at a very low falsepositive rate. Typically, the filters are trained with techniques that optimize accuracy or entropy, rather than perfor...
Wen-tau Yih, Joshua Goodman, Geoff Hulten
ICML
1997
IEEE
16 years 5 months ago
Robot Learning From Demonstration
The goal of robot learning from demonstration is to have a robot learn from watching a demonstration of the task to be performed. In our approach to learning from demonstration th...
Christopher G. Atkeson, Stefan Schaal
ICALT
2008
IEEE
15 years 11 months ago
Designing a Dynamic Bayesian Network for Modeling Students' Learning Styles
When using Learning Object Repositories, it is interesting to have mechanisms to select the more adequate objects for each student. For this kind of adaptation, it is important to...
Cristina Carmona, Gladys Castillo, Eva Millá...
SEMWEB
2012
Springer
14 years 19 days ago
How to deal with massively heterogeneous cultural heritage data - lessons learned in CultureSampo
Abstract. This paper presents the CultureSampo system from the viewpoint of publishing heterogeneous linked data as a service. Discussed are the problems of converting legacy data ...
Eetu Mäkelä, Eero Hyvönen, Tuukka R...