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» Predicate Invention and Learning from Positive Examples Only
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ICFCA
2007
Springer
14 years 1 months ago
A Parameterized Algorithm for Exploring Concept Lattices
Kuznetsov shows that Formal Concept Analysis (FCA) is a natural framework for learning from positive and negative examples. Indeed, the results of learning from positive examples (...
Peggy Cellier, Sébastien Ferré, Oliv...
ICMCS
2000
IEEE
170views Multimedia» more  ICMCS 2000»
13 years 12 months ago
Update Relevant Image Weights for Content-Based Image Retrieval using Support Vector Machines
Relevance feedback [1] has been a powerful tool for interactive Content-Based Image Retrieval (CBIR). During the retrieval process, the user selects the most relevant images and p...
Qi Tian, Pengyu Hong, Thomas S. Huang
COLT
2006
Springer
13 years 11 months ago
Teaching Randomized Learners
Abstract. The present paper introduces a new model for teaching randomized learners. Our new model, though based on the classical teaching dimension model, allows to study the infl...
Frank J. Balbach, Thomas Zeugmann
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
14 years 7 months ago
Practical learning from one-sided feedback
In many data mining applications, online labeling feedback is only available for examples which were predicted to belong to the positive class. Such applications include spam filt...
D. Sculley
ATAL
2006
Springer
13 years 11 months ago
Ontology-guided learning to improve communication between groups of agents
We present a general method for agents using ontologies as part of their knowledge representation to teach each other concepts to improve their communication and thus cooperation ...
Mohsen Afsharchi, Behrouz H. Far, Jörg Denzin...