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ECTEL
2010
Springer
14 years 10 months ago
GVIS: A Facility for Adaptively Mashing Up and Representing Open Learner Models
In this article we present an infrastructure for creating mash up and visual representations of the user profile that combine data from different sources. We explored this approach...
Luca Mazzola, Riccardo Mazza
ATAL
2006
Springer
15 years 4 months ago
A hierarchical approach to efficient reinforcement learning in deterministic domains
Factored representations, model-based learning, and hierarchies are well-studied techniques for improving the learning efficiency of reinforcement-learning algorithms in large-sca...
Carlos Diuk, Alexander L. Strehl, Michael L. Littm...
165
Voted

Book
498views
16 years 10 months ago
Machine Learning, Neural and Statistical Classification
This book covers several topics such as Classification, Classical Statistical Methods, Modern Statistical Techniques, Machine Learning of Rules and Trees, Neural Networks Methods ...
Ellis Horwood
80
Voted
ICCBR
2005
Springer
15 years 6 months ago
Learning Semantic Annotations for Textual Cases
Abstract. In this paper, we propose an approach to attach semantic annotations to textual cases for their representation. To achieve this goal, a framework that combines machine le...
Eni Mustafaraj, Martin Hoof, Bernd Freisleben
82
Voted
IJCAI
2001
15 years 2 months ago
Relational Learning via Propositional Algorithms: An Information Extraction Case Study
This paper develops a new paradigm for relational learning which allows for the representation and learning of relational information using propositional means. This paradigm sugg...
Dan Roth, Wen-tau Yih