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NLP
2000
14 years 22 days ago
Learning Rules for Large-Vocabulary Word Sense Disambiguation: A Comparison of Various Classifiers
In this article we compare the performance of various machine learning algorithms on the task of constructing word-sense disambiguation rules from data. The distinguishing characte...
Georgios Paliouras, Vangelis Karkaletsis, Ion Andr...
ICANN
2010
Springer
13 years 7 months ago
Dynamic Shape Learning and Forgetting
In this paper, we present a system capable of dynamically learning shapes in a way that also allows for the dynamic deletion of shapes already learned. It uses a self-balancing Bin...
Nikolaos Tsapanos, Anastasios Tefas, Ioannis Pitas
ESANN
2001
13 years 10 months ago
A divide-and-conquer learning architecture for predicting unknown motion
Time varying environments or model selection problems lead to crucial dilemmas in identification and control science. In this paper, we propose a modular prediction scheme consisti...
Patrice Wira, Jean-Philippe Urban, Julien Gresser
FLAIRS
2006
13 years 10 months ago
Full Restart Speeds Learning
Because many real-world problems can be represented and solved as constraint satisfaction problems, the development of effective, efficient constraint solvers is important. A solv...
Smiljana Petrovic, Susan L. Epstein
ECSQARU
2009
Springer
14 years 3 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...