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» Classifier Instability and Partitioning
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MCS
2005
Springer
14 years 13 days ago
Ensembles of Classifiers from Spatially Disjoint Data
We describe an ensemble learning approach that accurately learns from data that has been partitioned according to the arbitrary spatial requirements of a large-scale simulation whe...
Robert E. Banfield, Lawrence O. Hall, Kevin W. Bow...
FMCAD
2004
Springer
13 years 10 months ago
A Partitioning Methodology for BDD-Based Verification
The main challenge in BDD-based verification is dealing with the memory explosion problem during reachability analysis. In this paper we advocate a methodology to handle this probl...
Debashis Sahoo, Subramanian K. Iyer, Jawahar Jain,...
WIOPT
2010
IEEE
13 years 5 months ago
Static community detection algorithms for evolving networks
—Complex networks can often be divided in dense sub-networks called communities. Using a partition edit distance, we study how three community detection algorithms transform thei...
Thomas Aynaud, Jean-Loup Guillaume
TKDD
2008
113views more  TKDD 2008»
13 years 6 months ago
Privacy-preserving classification of vertically partitioned data via random kernels
We propose a novel privacy-preserving support vector machine (SVM) classifier for a data matrix A whose input feature columns are divided into groups belonging to different entiti...
Olvi L. Mangasarian, Edward W. Wild, Glenn Fung
TKDE
2010
183views more  TKDE 2010»
13 years 5 months ago
Filter-Based Data Partitioning for Training Multiple Classifier Systems
Rozita A. Dara, Masoud Makrehchi, Mohamed S. Kamel