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» Optimizing F-Measure with Support Vector Machines
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BMCBI
2006
110views more  BMCBI 2006»
13 years 7 months ago
Bias in error estimation when using cross-validation for model selection
Background: Cross-validation (CV) is an effective method for estimating the prediction error of a classifier. Some recent articles have proposed methods for optimizing classifiers...
Sudhir Varma, Richard Simon
ICML
2007
IEEE
14 years 8 months ago
Pegasos: Primal Estimated sub-GrAdient SOlver for SVM
We describe and analyze a simple and effective iterative algorithm for solving the optimization problem cast by Support Vector Machines (SVM). Our method alternates between stocha...
Shai Shalev-Shwartz, Yoram Singer, Nathan Srebro
MLG
2007
Springer
14 years 1 months ago
A Universal Kernel for Learning Regular Languages
We give a universal kernel that renders all the regular languages linearly separable. We are not able to compute this kernel efficiently and conjecture that it is intractable, but...
Leonid Kontorovich
ICCV
2003
IEEE
14 years 9 months ago
Landmark-based Shape Deformation with Topology-Preserving Constraints
This paper presents a novel approach for landmarkbased shape deformation, in which fitting error and shape difference are formulated into a support vector machine (SVM) regression...
Song Wang, Jim Xiuquan Ji, Zhi-Pei Liang
ICIP
2006
IEEE
14 years 9 months ago
Automatic Video Genre Categorization using Hierarchical SVM
This paper presents an automatic video genre categorization scheme based on the hierarchical ontology on video genres. Ten computable spatio-temporal features are extracted to dis...
Xun Yuan, Wei Lai, Tao Mei, Xian-Sheng Hua, Xiuqin...