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ALT
2006
Springer
14 years 5 months ago
Learning Linearly Separable Languages
This paper presents a novel paradigm for learning languages that consists of mapping strings to an appropriate high-dimensional feature space and learning a separating hyperplane i...
Leonid Kontorovich, Corinna Cortes, Mehryar Mohri
MLG
2007
Springer
14 years 3 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...
ICMLC
2010
Springer
13 years 6 months ago
A comparative study on two large-scale hierarchical text classification tasks' solutions
: Patent classification is a large scale hierarchical text classification (LSHTC) task. Though comprehensive comparisons, either learning algorithms or feature selection strategies...
Jian Zhang, Hai Zhao, Bao-Liang Lu
BMCBI
2008
185views more  BMCBI 2008»
13 years 9 months ago
Mining clinical relationships from patient narratives
Background: The Clinical E-Science Framework (CLEF) project has built a system to extract clinically significant information from the textual component of medical records in order...
Angus Roberts, Robert J. Gaizauskas, Mark Hepple, ...
CVPR
2008
IEEE
14 years 11 months ago
Margin-based discriminant dimensionality reduction for visual recognition
Nearest neighbour classifiers and related kernel methods often perform poorly in high dimensional problems because it is infeasible to include enough training samples to cover the...
Hakan Cevikalp, Bill Triggs, Frédéri...