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» Relevance Vector Machine Analysis of Functional Neuroimages
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ICCAD
1999
IEEE
84views Hardware» more  ICCAD 1999»
15 years 1 months ago
Improving coverage analysis and test generation for large designs
State space techniques have proven to be useful for measuring and improving the coverage of test vectors that are used during functional validation via simulation. By comparing th...
Jules P. Bergmann, Mark Horowitz
78
Voted
DSS
2008
186views more  DSS 2008»
14 years 9 months ago
A machine learning approach to web page filtering using content and structure analysis
As the Web continues to grow, it has become increasingly difficult to search for relevant information using traditional search engines. Topic-specific search engines provide an al...
Michael Chau, Hsinchun Chen
JMLR
2012
13 years 2 days ago
Sparse Additive Machine
We develop a high dimensional nonparametric classification method named sparse additive machine (SAM), which can be viewed as a functional version of support vector machine (SVM)...
Tuo Zhao, Han Liu
JMLR
2008
133views more  JMLR 2008»
14 years 9 months ago
Algorithms for Sparse Linear Classifiers in the Massive Data Setting
Classifiers favoring sparse solutions, such as support vector machines, relevance vector machines, LASSO-regression based classifiers, etc., provide competitive methods for classi...
Suhrid Balakrishnan, David Madigan
WSCG
2004
188views more  WSCG 2004»
14 years 11 months ago
Recognition of Motor Imagery Electroencephalography Using Independent Component Analysis and Machine Classifiers
Motor imagery electroencephalography (EEG), which embodies cortical potentials during mental simulation of left or right finger lifting tasks, can be used as neural input signals ...
Chih-I. Hung, Po-Lei Lee, Yu-Te Wu, Hui-Yun Chen, ...