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» Efficient kernel feature extraction for massive data sets
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NIPS
2004
13 years 9 months ago
Efficient Kernel Discriminant Analysis via QR Decomposition
Linear Discriminant Analysis (LDA) is a well-known method for feature extraction and dimension reduction. It has been used widely in many applications such as face recognition. Re...
Tao Xiong, Jieping Ye, Qi Li, Ravi Janardan, Vladi...
AAAI
2007
13 years 10 months ago
Recognizing Textual Entailment Using a Subsequence Kernel Method
We present a novel approach to recognizing Textual nt. Structural features are constructed from abstract tree descriptions, which are automatically extracted from syntactic depend...
Rui Wang 0005, Günter Neumann
MLDM
2007
Springer
14 years 1 months ago
Nonlinear Feature Selection by Relevance Feature Vector Machine
Support vector machine (SVM) has received much attention in feature selection recently because of its ability to incorporate kernels to discover nonlinear dependencies between feat...
Haibin Cheng, Haifeng Chen, Guofei Jiang, Kenji Yo...

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...
VISAPP
2008
13 years 9 months ago
Continuous Learning of Simple Visual Concepts Using Incremental Kernel Density Estimation
In this paper we propose a method for continuous learning of simple visual concepts. The method continuously associates words describing observed scenes with automatically extracte...
Danijel Skocaj, Matej Kristan, Ales Leonardis