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ATAL
2009
Springer
13 years 11 months ago
Improved approximation of interactive dynamic influence diagrams using discriminative model updates
Interactive dynamic influence diagrams (I-DIDs) are graphical models for sequential decision making in uncertain settings shared by other agents. Algorithms for solving I-DIDs fac...
Prashant Doshi, Yifeng Zeng
ACSAC
2001
IEEE
13 years 11 months ago
Mining Alarm Clusters to Improve Alarm Handling Efficiency
It is a well-known problem that intrusion detection systems overload their human operators by triggering thousands of alarms per day. As a matter of fact, we have been asked by on...
Klaus Julisch
STOC
2003
ACM
141views Algorithms» more  STOC 2003»
14 years 7 months ago
Better streaming algorithms for clustering problems
We study clustering problems in the streaming model, where the goal is to cluster a set of points by making one pass (or a few passes) over the data using a small amount of storag...
Moses Charikar, Liadan O'Callaghan, Rina Panigrahy
SIGMETRICS
2002
ACM
104views Hardware» more  SIGMETRICS 2002»
13 years 7 months ago
Improving cluster availability using workstation validation
We demonstrate a framework for improving the availability of cluster based Internet services. Our approach models Internet services as a collection of interconnected components, e...
Taliver Heath, Richard P. Martin, Thu D. Nguyen
KDD
2005
ACM
166views Data Mining» more  KDD 2005»
14 years 8 months ago
A general model for clustering binary data
Clustering is the problem of identifying the distribution of patterns and intrinsic correlations in large data sets by partitioning the data points into similarity classes. This p...
Tao Li