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» Learning the k in k-means
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KDD
2004
ACM
124views Data Mining» more  KDD 2004»
14 years 7 months ago
Eigenspace-based anomaly detection in computer systems
We report on an automated runtime anomaly detection method at the application layer of multi-node computer systems. Although several network management systems are available in th...
Hisashi Kashima, Tsuyoshi Idé
CHI
2005
ACM
14 years 7 months ago
AppLens and launchTile: two designs for one-handed thumb use on small devices
We present two interfaces to support one-handed thumb use for PDAs and cell phones. Both use Scalable User Interface (ScUI) techniques to support multiple devices with different r...
Amy K. Karlson, Benjamin B. Bederson, John SanGiov...
STOC
2007
ACM
112views Algorithms» more  STOC 2007»
14 years 7 months ago
Smooth sensitivity and sampling in private data analysis
We introduce a new, generic framework for private data analysis. The goal of private data analysis is to release aggregate information about a data set while protecting the privac...
Kobbi Nissim, Sofya Raskhodnikova, Adam Smith
SIGMOD
2004
ACM
209views Database» more  SIGMOD 2004»
14 years 7 months ago
MAIDS: Mining Alarming Incidents from Data Streams
Real-time surveillance systems, network and telecommunication systems, and other dynamic processes often generate tremendous (potentially infinite) volume of stream data. Effectiv...
Y. Dora Cai, David Clutter, Greg Pape, Jiawei Han,...
MOBISYS
2008
ACM
14 years 7 months ago
Behavioral detection of malware on mobile handsets
A novel behavioral detection framework is proposed to detect mobile worms, viruses and Trojans, instead of the signature-based solutions currently available for use in mobile devi...
Abhijit Bose, Xin Hu, Kang G. Shin, Taejoon Park