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ICML
2005
IEEE
16 years 7 months ago
Comparing clusterings: an axiomatic view
This paper views clusterings as elements of a lattice. Distances between clusterings are analyzed in their relationship to the lattice. From this vantage point, we first give an a...
Marina Meila
SAC
2010
ACM
16 years 1 months ago
Recovering uncertain mappings through structural validation and aggregation with the MoTo system
We present an automated ontology matching methodology, supported by various machine learning techniques, as implemented in the system MoTo. The methodology is twotiered. On the ï¬...
Floriana Esposito, Nicola Fanizzi, Claudia d'Amato
COLT
2010
Springer
15 years 4 months ago
Principal Component Analysis with Contaminated Data: The High Dimensional Case
We consider the dimensionality-reduction problem (finding a subspace approximation of observed data) for contaminated data in the high dimensional regime, where the number of obse...
Huan Xu, Constantine Caramanis, Shie Mannor
ICML
2005
IEEE
16 years 7 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
ICML
2003
IEEE
16 years 7 months ago
Learning Mixture Models with the Latent Maximum Entropy Principle
We present a new approach to estimating mixture models based on a new inference principle we have proposed: the latent maximum entropy principle (LME). LME is different both from ...
Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin...