5114 search results - page 575 / 1023 » Learning for Evolutionary Design |
210
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KDD
2009
ACM
15 years 11 months ago
2009
ACM
Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that c...
221
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KDD
2009
ACM
16 years 7 months ago
2009
ACM
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
180
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EUROCAST
2007
Springer
16 years 1 months ago
2007
Springer
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
176
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ILP
2003
Springer
16 years 4 days ago
2003
Springer
In the case of concept learning from positive and negative examples, it is rarely possible to find a unique discriminating conjunctive rule; in most cases, a disjunctive descripti...
191
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SAGA
2001
Springer
15 years 11 months ago
2001
Springer
Inductive inference can be considered as one of the fundamental paradigms of algorithmic learning theory. We survey results recently obtained and show their impact to potential ap...