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» Diversified SVM Ensembles for Large Data Sets
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KDD
2000
ACM
133views Data Mining» more  KDD 2000»
15 years 9 months ago
Data selection for support vector machine classifiers
The problem of extracting a minimal number of data points from a large dataset, in order to generate a support vector machine (SVM) classifier, is formulated as a concave minimiza...
Glenn Fung, Olvi L. Mangasarian
TIP
2010
145views more  TIP 2010»
15 years 23 days ago
Joint Manifolds for Data Fusion
The emergence of low-cost sensing architectures for diverse modalities has made it possible to deploy sensor networks that capture a single event from a large number of vantage po...
Mark A. Davenport, Chinmay Hegde, Marco F. Duarte,...
NIPS
2000
15 years 7 months ago
A New Approximate Maximal Margin Classification Algorithm
A new incremental learning algorithm is described which approximates the maximal margin hyperplane w.r.t. norm p 2 for a set of linearly separable data. Our algorithm, called alm...
Claudio Gentile
WWW
2009
ACM
16 years 6 months ago
An axiomatic approach for result diversification
Understanding user intent is key to designing an effective ranking system in a search engine. In the absence of any explicit knowledge of user intent, search engines want to diver...
Sreenivas Gollapudi, Aneesh Sharma
IJCNN
2008
IEEE
16 years 14 days ago
Support vector machines and dynamic time warping for time series
— Effective use of support vector machines (SVMs) in classification necessitates the appropriate choice of a kernel. Designing problem specific kernels involves the definition...
Steinn Gudmundsson, Thomas Philip Runarsson, Sven ...