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» Boosting strategy for classification
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GLOBECOM
2008
IEEE
13 years 10 months ago
On the Impact of Caching for High Performance Packet Classifiers
Hash functions have a space complexity of O(n) and a possible time complexity of O(1). Thus, packet classifiers exploit hashing to achieve packet classification in wire speed. Esp...
Harald Widiger, Andreas Tockhorn, Dirk Timmermann
PPOPP
2010
ACM
14 years 7 months ago
Using data structure knowledge for efficient lock generation and strong atomicity
To achieve high-performance on multicore systems, sharedmemory parallel languages must efficiently implement atomic operations. The commonly used and studied paradigms for atomici...
Gautam Upadhyaya, Samuel P. Midkiff, Vijay S. Pai
CVPR
2006
IEEE
15 years 9 days ago
Applying Ensembles of Multilinear Classifiers in the Frequency Domain
Ensemble methods such as bootstrap, bagging or boosting have had a considerable impact on recent developments in machine learning, pattern recognition and computer vision. Theoret...
Christian Bauckhage, Thomas Käster, John K. T...
BMCBI
2010
150views more  BMCBI 2010»
13 years 10 months ago
AMS 3.0: prediction of post-translational modifications
Background: We present here the recent update of AMS algorithm for identification of post-translational modification (PTM) sites in proteins based only on sequence information, us...
Subhadip Basu, Dariusz Plewczynski
ICPR
2006
IEEE
14 years 11 months ago
A New Data Selection Principle for Semi-Supervised Incremental Learning
Current semi-supervised incremental learning approaches select unlabeled examples with predicted high confidence for model re-training. We show that for many applications this dat...
Alexander I. Rudnicky, Rong Zhang