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ICML
2004
IEEE
16 years 3 months ago
Kernel conditional random fields: representation and clique selection
Kernel conditional random fields (KCRFs) are introduced as a framework for discriminative modeling of graph-structured data. A representer theorem for conditional graphical models...
John D. Lafferty, Xiaojin Zhu, Yan Liu
GCB
2010
Springer
204views Biometrics» more  GCB 2010»
15 years 12 days ago
Learning Pathway-based Decision Rules to Classify Microarray Cancer Samples
: Despite recent advances in DNA chip technology current microarray gene expression studies are still affected by high noise levels, small sample sizes and large numbers of uninfor...
Enrico Glaab, Jonathan M. Garibaldi, Natalio Krasn...
120
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ECCV
2010
Springer
15 years 6 months ago
Predicting Facial Beauty without Landmarks
A fundamental task in artificial intelligence and computer vision is to build machines that can behave like a human in recognizing a broad range of visual concepts. This paper aims...
IFIP12
2010
15 years 27 days ago
Learning the Preferences of News Readers with SVM and Lasso Ranking
We attack the task of predicting which news-stories are more appealing to a given audience by comparing ‘most popular stories’, gathered from various online news outlets, over ...
Elena Hensinger, Ilias N. Flaounas, Nello Cristian...
BMCBI
2008
114views more  BMCBI 2008»
15 years 2 months ago
Combining classifiers for improved classification of proteins from sequence or structure
Background: Predicting a protein's structural or functional class from its amino acid sequence or structure is a fundamental problem in computational biology. Recently, there...
Iain Melvin, Jason Weston, Christina S. Leslie, Wi...