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» Markov Blanket Feature Selection for Support Vector Machines
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CIKM
2008
Springer
13 years 9 months ago
Learning a two-stage SVM/CRF sequence classifier
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...
Guilherme Hoefel, Charles Elkan
MLG
2007
Springer
14 years 1 months ago
Weighted Substructure Mining for Image Analysis
1 In web-related applications of image categorization, it is desirable to derive an interpretable classification rule with high accuracy. Using the bag-of-words representation and...
Sebastian Nowozin, Koji Tsuda, Takeaki Uno, Taku K...
BMCBI
2010
146views more  BMCBI 2010»
13 years 7 months ago
Nonnegative principal component analysis for mass spectral serum profiles and biomarker discovery
Background: As a novel cancer diagnostic paradigm, mass spectroscopic serum proteomic pattern diagnostics was reported superior to the conventional serologic cancer biomarkers. Ho...
Henry Han
ACL
2003
13 years 9 months ago
Fast Methods for Kernel-Based Text Analysis
Kernel-based learning (e.g., Support Vector Machines) has been successfully applied to many hard problems in Natural Language Processing (NLP). In NLP, although feature combinatio...
Taku Kudo, Yuji Matsumoto
ECCV
2002
Springer
14 years 9 months ago
Learning to Parse Pictures of People
The detection of people is one of the foremost problems for indexing, browsing and retrieval of video. The main difficulty is the large appearance variations caused by action, clot...
Rémi Ronfard, Cordelia Schmid, Bill Triggs