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ICPR
2000
IEEE
16 years 6 months ago
Data Condensation in Large Databases by Incremental Learning with Support Vector Machines
An algorithmfor data condensation using support vector machines (SVM's)is presented. The algorithm extracts datapoints lying close to the class boundaries,whichform a much re...
Pabitra Mitra, C. A. Murthy, Sankar K. Pal
LFCS
1992
Springer
15 years 9 months ago
Machine Learning of Higher Order Programs
A generator program for a computable function (by definition) generates an infinite sequence of programs all but finitely many of which compute that function. Machine learning of ...
Ganesh Baliga, John Case, Sanjay Jain, Mandayam Su...
JMLR
2002
89views more  JMLR 2002»
15 years 4 months ago
The Set Covering Machine
We extend the classical algorithms of Valiant and Haussler for learning compact conjunctions and disjunctions of Boolean attributes to allow features that are constructed from the...
Mario Marchand, John Shawe-Taylor
ECML
2003
Springer
15 years 10 months ago
Support Vector Machines with Example Dependent Costs
Abstract. Classical learning algorithms from the fields of artificial neural networks and machine learning, typically, do not take any costs into account or allow only costs depe...
Ulf Brefeld, Peter Geibel, Fritz Wysotzki
KDD
2006
ACM
180views Data Mining» more  KDD 2006»
16 years 5 months ago
Learning the unified kernel machines for classification
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang