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SIGOPS
2008
146views more  SIGOPS 2008»
13 years 8 months ago
Vigilant: out-of-band detection of failures in virtual machines
What do our computer systems do all day? How do we make sure they continue doing it when failures occur? Traditional approaches to answering these questions often involve inband m...
Dan Pelleg, Muli Ben-Yehuda, Richard Harper, Lisa ...
KDD
2012
ACM
205views Data Mining» more  KDD 2012»
11 years 10 months ago
Rank-loss support instance machines for MIML instance annotation
Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
Forrest Briggs, Xiaoli Z. Fern, Raviv Raich
ESWA
2006
122views more  ESWA 2006»
13 years 8 months ago
Transmembrane segments prediction and understanding using support vector machine and decision tree
In recent years, there have been many studies focusing on improving the accuracy of prediction of transmembrane segments, and many significant results have been achieved. In spite...
Jieyue He, Hae-Jin Hu, Robert W. Harrison, Phang C...
ADCS
2004
13 years 9 months ago
Phrases and Feature Selection in E-Mail Classification
In this paper we study the effectiveness of using a phrase-based representation in e-mail classification, and the affect this approach has on a number of machine learning algorithm...
Elisabeth Crawford, Irena Koprinska, Jon Patrick
ICDM
2009
IEEE
137views Data Mining» more  ICDM 2009»
14 years 2 months ago
Set-Based Boosting for Instance-Level Transfer
—The success of transfer to improve learning on a target task is highly dependent on the selected source data. Instance-based transfer methods reuse data from the source tasks to...
Eric Eaton, Marie desJardins