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74
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JMLR
2010
115views more  JMLR 2010»
14 years 4 months ago
Fast and Scalable Local Kernel Machines
A computationally efficient approach to local learning with kernel methods is presented. The Fast Local Kernel Support Vector Machine (FaLK-SVM) trains a set of local SVMs on redu...
Nicola Segata, Enrico Blanzieri
87
Voted
ICNC
2005
Springer
15 years 3 months ago
Support Vector Based Prototype Selection Method for Nearest Neighbor Rules
The Support vector machines derive the class decision hyper planes from a few, selected prototypes, the support vectors (SVs) according to the principle of structure risk minimizat...
Yuangui Li, Zhonghui Hu, Yunze Cai, Weidong Zhang
BMCBI
2005
155views more  BMCBI 2005»
14 years 9 months ago
Mining protein function from text using term-based support vector machines
Background: Text mining has spurred huge interest in the domain of biology. The goal of the BioCreAtIvE exercise was to evaluate the performance of current text mining systems. We...
Simon B. Rice, Goran Nenadic, Benjamin J. Stapley
80
Voted
ICML
2006
IEEE
15 years 10 months ago
Two-dimensional solution path for support vector regression
Recently, a very appealing approach was proposed to compute the entire solution path for support vector classification (SVC) with very low extra computational cost. This approach ...
Gang Wang, Dit-Yan Yeung, Frederick H. Lochovsky
CVPR
2008
IEEE
15 years 11 months ago
Enforcing non-positive weights for stable support vector tracking
In this paper we demonstrate that the support vector tracking (SVT) framework first proposed by Avidan is equivalent to the canonical Lucas-Kanade (LK) algorithm with a weighted E...
Simon Lucey