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BMCBI
2007
157views more  BMCBI 2007»
14 years 9 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...
83
Voted
SADFE
2009
IEEE
15 years 4 months ago
File Fragment Classification-The Case for Specialized Approaches
Increasingly advances in file carving, memory analysis and network forensics requires the ability to identify the underlying type of a file given only a file fragment. Work to dat...
Vassil Roussev, Simson L. Garfinkel
70
Voted
ICML
2006
IEEE
15 years 10 months ago
Bayesian regression with input noise for high dimensional data
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
Jo-Anne Ting, Aaron D'Souza, Stefan Schaal
JSAC
2010
146views more  JSAC 2010»
14 years 4 months ago
NLOS identification and mitigation for localization based on UWB experimental data
Abstract--Sensor networks can benefit greatly from locationawareness, since it allows information gathered by the sensors to be tied to their physical locations. Ultra-wide bandwid...
Stefano Maranò, Wesley M. Gifford, Henk Wym...
APNOMS
2008
Springer
14 years 11 months ago
Empirical Analysis of Application-Level Traffic Classification Using Supervised Machine Learning
Accurate application traffic classification and identification are important for network monitoring and analysis. The accuracy of traditional Internet application traffic classific...
Byungchul Park, Young J. Won, Mi-Jung Choi, Myung-...