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CCS
2009
ACM
15 years 11 months ago
Active learning for network intrusion detection
Anomaly detection for network intrusion detection is usually considered an unsupervised task. Prominent techniques, such as one-class support vector machines, learn a hypersphere ...
Nico Görnitz, Marius Kloft, Konrad Rieck, Ulf...
ACSAC
2006
IEEE
15 years 10 months ago
Addressing SMTP-Based Mass-Mailing Activity within Enterprise Networks
Malicious mass-mailing activity on the Internet is a serious and continuing threat that includes mass-mailing worms, spam, and phishing. A mechanism commonly used to deliver such ...
David Whyte, Paul C. van Oorschot, Evangelos Krana...
HRI
2010
ACM
15 years 9 months ago
Transparent active learning for robots
—This research aims to enable robots to learn from human teachers. Motivated by human social learning, we believe that a transparent learning process can help guide the human tea...
Crystal Chao, Maya Cakmak, Andrea Lockerd Thomaz
MICCAI
1999
Springer
15 years 8 months ago
Statistical Segmentation of fMRI Activations Using Contextual Clustering
Abstract. A central problem in the analysis of functional magnetic resonance imaging (fMRI) data is the reliable detection and segmentation of activated areas. Often this goal is a...
Eero Salli, Ari Visa, Hannu J. Aronen, Antti Korve...
AAAI
2008
15 years 6 months ago
Feature Selection for Activity Recognition in Multi-Robot Domains
In multi-robot settings, activity recognition allows a robot to respond intelligently to the other robots in its environment. Conditional random fields are temporal models that ar...
Douglas L. Vail, Manuela M. Veloso