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» Learning Rule Representations from Boolean Data
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ICML
2005
IEEE
16 years 1 months ago
Supervised versus multiple instance learning: an empirical comparison
We empirically study the relationship between supervised and multiple instance (MI) learning. Algorithms to learn various concepts have been adapted to the MI representation. Howe...
Soumya Ray, Mark Craven
OGAI
1993
15 years 4 months ago
Combining Neural Networks and Fuzzy Controllers
Fuzzy controllers are designed to work with knowledge in the form of linguistic control rules. But the translation of these linguistic rules into the framework of fuzzy set theory ...
Detlef Nauck, Frank Klawonn, Rudolf Kruse
89
Voted
KDD
2004
ACM
113views Data Mining» more  KDD 2004»
16 years 1 months ago
Learning spatially variant dissimilarity (SVaD) measures
Clustering algorithms typically operate on a feature vector representation of the data and find clusters that are compact with respect to an assumed (dis)similarity measure betwee...
Krishna Kummamuru, Raghu Krishnapuram, Rakesh Agra...
KDD
2007
ACM
154views Data Mining» more  KDD 2007»
16 years 1 months ago
Canonicalization of database records using adaptive similarity measures
It is becoming increasingly common to construct databases from information automatically culled from many heterogeneous sources. For example, a research publication database can b...
Aron Culotta, Michael L. Wick, Robert Hall, Matthe...
UAI
2008
15 years 2 months ago
Learning Inclusion-Optimal Chordal Graphs
Chordal graphs can be used to encode dependency models that are representable by both directed acyclic and undirected graphs. This paper discusses a very simple and efficient algo...
Vincent Auvray, Louis Wehenkel