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GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
13 years 6 months ago
Informative sampling for large unbalanced data sets
Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
Zhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Jos...
IPM
2008
100views more  IPM 2008»
13 years 4 months ago
Query-level loss functions for information retrieval
Many machine learning technologies such as support vector machines, boosting, and neural networks have been applied to the ranking problem in information retrieval. However, since...
Tao Qin, Xu-Dong Zhang, Ming-Feng Tsai, De-Sheng W...
NIPS
2003
13 years 6 months ago
Nonlinear Filtering of Electron Micrographs by Means of Support Vector Regression
Nonlinear filtering can solve very complex problems, but typically involve very time consuming calculations. Here we show that for filters that are constructed as a RBF network ...
Roland Vollgraf, Michael Scholz, Ian A. Meinertzha...
BMCBI
2006
112views more  BMCBI 2006»
13 years 4 months ago
Protein disorder prediction by condensed PSSM considering propensity for order or disorder
Background: More and more disordered regions have been discovered in protein sequences, and many of them are found to be functionally significant. Previous studies reveal that dis...
Chung-Tsai Su, Chien-Yu Chen, Yu-Yen Ou
AIR
1998
160views more  AIR 1998»
13 years 4 months ago
Automatic Plankton Image Recognition
Plankton form the base of the food chain in the ocean and are fundamental to marine ecosystem dynamics. The rapid mapping of plankton abundance together with taxonomic and size com...
Xiaoou Tang, W. Kenneth Stewart, He Huang, Scott M...