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» Learning and using relational theories
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JIRS
2000
144views more  JIRS 2000»
15 years 6 months ago
An Integrated Approach of Learning, Planning, and Execution
Agents (hardware or software) that act autonomously in an environment have to be able to integrate three basic behaviors: planning, execution, and learning. This integration is man...
Ramón García-Martínez, Daniel...
ECML
2006
Springer
15 years 10 months ago
TildeCRF: Conditional Random Fields for Logical Sequences
Abstract. Conditional Random Fields (CRFs) provide a powerful instrument for labeling sequences. So far, however, CRFs have only been considered for labeling sequences over flat al...
Bernd Gutmann, Kristian Kersting
189
Voted
ML
1998
ACM
131views Machine Learning» more  ML 1998»
15 years 6 months ago
Learning from Examples and Membership Queries with Structured Determinations
It is well known that prior knowledge or bias can speed up learning, at least in theory. It has proved di cult to make constructive use of prior knowledge, so that approximately c...
Prasad Tadepalli, Stuart J. Russell
217
Voted
KDD
2008
ACM
137views Data Mining» more  KDD 2008»
16 years 7 months ago
Learning classifiers from only positive and unlabeled data
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Charles Elkan, Keith Noto
SBIA
2004
Springer
16 years 2 days ago
Learning with Drift Detection
Abstract. Most of the work in machine learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
João Gama, Pedro Medas, Gladys Castillo, Pe...