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» Optimal feature selection for support vector machines
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ICML
2007
IEEE
14 years 8 months ago
Solving multiclass support vector machines with LaRank
Optimization algorithms for large margin multiclass recognizers are often too costly to handle ambitious problems with structured outputs and exponential numbers of classes. Optim...
Antoine Bordes, Jason Weston, Léon Bottou, ...

Publication
352views
13 years 1 months ago
A Contourlet Transform Feature Extraction Scheme for Ultrasound Thyroid Texture Classification
Ultrasonography is an invaluable and widely used medical imaging tool. Nevertheless, automatic texture analysis on ultrasound images remains a challenging issue. This work presen...
Stamos Katsigiannis, Eystratios G. Keramidas, Dimi...
AAAI
2008
13 years 10 months ago
In-the-Dark Network Traffic Classification Using Support Vector Machines
This work addresses the problem of in-the-dark traffic classification for TCP sessions, an important problem in network management. An innovative use of support vector machines (S...
William H. Turkett Jr., Andrew V. Karode, Errin W....
COLING
2002
13 years 7 months ago
Extracting Word Sequence Correspondences with Support Vector Machines
This paper proposes a learning and extracting method of word sequence correspondences from non-aligned parallel corpora with Support Vector Machines, which have high ability of th...
Kengo Sato, Hiroaki Saito
ICMCS
2006
IEEE
105views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Entropy and Memory Constrained Vector Quantization with Separability Based Feature Selection
An iterative model selection algorithm is proposed. The algorithm seeks relevant features and an optimal number of codewords (or codebook size) as part of the optimization. We use...
Sangho Yoon, Robert M. Gray