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SIGIR
2006
ACM
15 years 3 months ago
Large scale semi-supervised linear SVMs
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
Vikas Sindhwani, S. Sathiya Keerthi
AAAI
2006
14 years 11 months ago
Predicting Electricity Distribution Feeder Failures Using Machine Learning Susceptibility Analysis
A Machine Learning (ML) System known as ROAMS (Ranker for Open-Auto Maintenance Scheduling) was developed to create failure-susceptibility rankings for almost one thousand 13.8kV-...
Philip Gross, Albert Boulanger, Marta Arias, David...
KSEM
2009
Springer
15 years 4 months ago
A Competitive Learning Approach to Instance Selection for Support Vector Machines
Abstract. Support Vector Machines (SVM) have been applied successfully in a wide variety of fields in the last decade. The SVM problem is formulated as a convex objective function...
Mario Zechner, Michael Granitzer
68
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CIKM
2008
Springer
14 years 11 months ago
Suppressing outliers in pairwise preference ranking
Many of the recently proposed algorithms for learning feature-based ranking functions are based on the pairwise preference framework, in which instead of taking documents in isola...
Vitor R. Carvalho, Jonathan L. Elsas, William W. C...
ICCV
1999
IEEE
15 years 11 months ago
Control in a 3D Reconstruction System using Selective Perception
This paper presents a control structure for general purpose image understanding that addresses both the high level of uncertainty in local hypotheses and the computational complex...
Maurício Marengoni, Allen R. Hanson, Shlomo...