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ICPR
2008
IEEE
14 years 2 months ago
RANSAC-SVM for large-scale datasets
Support Vector Machines (SVMs), though accurate, are still difficult to solve large-scale applications, due to the computational and storage requirement. To relieve this problem,...
Kenji Watanabe, Takio Kurita
MINENET
2006
ACM
14 years 1 months ago
SVM learning of IP address structure for latency prediction
We examine the ability to exploit the hierarchical structure of Internet addresses in order to endow network agents with predictive capabilities. Specifically, we consider Suppor...
Robert Beverly, Karen R. Sollins, Arthur Berger
BMCBI
2011
12 years 11 months ago
Elastic SCAD as a novel penalization method for SVM classification tasks in high-dimensional data
Background: Classification and variable selection play an important role in knowledge discovery in highdimensional data. Although Support Vector Machine (SVM) algorithms are among...
Natalia Becker, Grischa Toedt, Peter Lichter, Axel...
ICRA
2008
IEEE
185views Robotics» more  ICRA 2008»
14 years 2 months ago
Human detection using multimodal and multidimensional features
— This paper presents a novel human detection method based on a Bayesian fusion approach using laser range data and camera images. Laser range data analysis groups data points wi...
Luciano Spinello, Roland Siegwart
KDD
2002
ACM
160views Data Mining» more  KDD 2002»
14 years 8 months ago
Scaling multi-class support vector machines using inter-class confusion
Support vector machines (SVMs) excel at two-class discriminative learning problems. They often outperform generative classifiers, especially those that use inaccurate generative m...
Shantanu Godbole, Sunita Sarawagi, Soumen Chakraba...