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» Sampling Techniques for Kernel Methods
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WAIM
2009
Springer
15 years 9 months ago
Probabilistic Threshold Range Aggregate Query Processing over Uncertain Data
Large amount of uncertain data is inherent in many novel and important applications such as sensor data analysis and mobile data management. A probabilistic threshold range aggrega...
Shuxiang Yang, Wenjie Zhang, Ying Zhang, Xuemin Li...
108
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SOFSEM
2001
Springer
15 years 7 months ago
How Can Computer Science Contribute to Knowledge Discovery?
Knowledge discovery, that is, to analyze a given massive data set and derive or discover some knowledge from it, has been becoming a quite important subject in several fields incl...
Osamu Watanabe
ICDM
2006
IEEE
131views Data Mining» more  ICDM 2006»
15 years 9 months ago
Dimension Reduction for Supervised Ordering
Ordered lists of objects are widely used as representational forms. Such ordered objects include Web search results and best-seller lists. Techniques for processing such ordinal d...
Toshihiro Kamishima, Shotaro Akaho
TOMACS
2002
113views more  TOMACS 2002»
15 years 2 months ago
Simulating heavy tailed processes using delayed hazard rate twisting
Consider the problem of estimating the small probability that the maximum of a random walk exceeds a large threshold, when the process has a negative drift and the underlying rand...
Sandeep Juneja, Perwez Shahabuddin
BMCBI
2007
157views more  BMCBI 2007»
15 years 2 months ago
Statistical learning of peptide retention behavior in chromatographic separations: a new kernel-based approach for computational
Background: High-throughput peptide and protein identification technologies have benefited tremendously from strategies based on tandem mass spectrometry (MS/MS) in combination wi...
Nico Pfeifer, Andreas Leinenbach, Christian G. Hub...