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» Feature selection for linear support vector machines
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SDM
2010
SIAM
151views Data Mining» more  SDM 2010»
13 years 9 months ago
Fast Stochastic Frank-Wolfe Algorithms for Nonlinear SVMs
The high computational cost of nonlinear support vector machines has limited their usability for large-scale problems. We propose two novel stochastic algorithms to tackle this pr...
Hua Ouyang, Alexander Gray
ICML
2010
IEEE
13 years 9 months ago
Learning Fast Approximations of Sparse Coding
In Sparse Coding (SC), input vectors are reconstructed using a sparse linear combination of basis vectors. SC has become a popular method for extracting features from data. For a ...
Karol Gregor, Yann LeCun
ICADL
2004
Springer
137views Education» more  ICADL 2004»
14 years 1 months ago
Using Content-Based and Link-Based Analysis in Building Vertical Search Engines
This paper reports our research in the Web page filtering process in specialized search engine development. We propose a machine-learning-based approach that combines Web content a...
Michael Chau, Hsinchun Chen
CIDM
2009
IEEE
13 years 12 months ago
Gender identification from E-mails
In this paper, we investigate the topic of gender identification for short length, multi-genre, content-free e-mails. We introduce for the first time (to our knowledge), psycholing...
Na Cheng, Xiaoling Chen, R. Chandramouli, K. P. Su...
CIBCB
2006
IEEE
14 years 2 months ago
A Model-Free Greedy Gene Selection for Microarray Sample Class Prediction
— Microarray data analysis is notoriously challenging as it involves a huge number of genes compared to only a limited number of samples. Gene selection, to detect the most signi...
Yi Shi, Zhipeng Cai, Lizhe Xu, Wei Ren, Randy Goeb...