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ICDM
2005
IEEE
135views Data Mining» more  ICDM 2005»
15 years 9 months ago
Bit Reduction Support Vector Machine
Abstract— Support vector machines are very accurate classifiers and have been widely used in many applications. However, the training and to a lesser extent prediction time of s...
Tong Luo, Lawrence O. Hall, Dmitry B. Goldgof, And...
136
Voted
SP
2010
IEEE
187views Security Privacy» more  SP 2010»
15 years 8 months ago
Outside the Closed World: On Using Machine Learning for Network Intrusion Detection
Abstract—In network intrusion detection research, one popular strategy for finding attacks is monitoring a network’s activity for anomalies: deviations from profiles of norma...
Robin Sommer, Vern Paxson
PKDD
2004
Springer
324views Data Mining» more  PKDD 2004»
15 years 9 months ago
Orange: From Experimental Machine Learning to Interactive Data Mining
Abstract. Orange (www.ailab.si/orange) is a suite for machine learning and data mining. It can be used though scripting in Python or with visual programming in Orange Canvas using ...
Janez Demsar, Blaz Zupan, Gregor Leban, Tomaz Curk
APPROX
2009
Springer
163views Algorithms» more  APPROX 2009»
15 years 10 months ago
The Power of Preemption on Unrelated Machines and Applications to Scheduling Orders
Abstract. Scheduling jobs on unrelated parallel machines so as to minimize the makespan is one of the basic, well-studied problems in the area of machine scheduling. In the first ...
José R. Correa, Martin Skutella, José...
WWIC
2010
Springer
193views Communications» more  WWIC 2010»
15 years 8 months ago
0day Anomaly Detection Made Possible Thanks to Machine Learning
Abstract. This paper proposes new cognitive algorithms and mechanisms for detecting 0day attacks targeting the Internet and its communication performances and behavior. For this pu...
Philippe Owezarski, Johan Mazel, Yann Labit