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SIGMOD
2001
ACM
142views Database» more  SIGMOD 2001»
16 years 6 months ago
Outlier Detection for High Dimensional Data
The outlier detection problem has important applications in the eld of fraud detection, network robustness analysis, and intrusion detection. Most such applications are high dimen...
Charu C. Aggarwal, Philip S. Yu
PODS
2006
ACM
122views Database» more  PODS 2006»
16 years 6 months ago
Space- and time-efficient deterministic algorithms for biased quantiles over data streams
Skew is prevalent in data streams, and should be taken into account by algorithms that analyze the data. The problem of finding "biased quantiles"-- that is, approximate...
Graham Cormode, Flip Korn, S. Muthukrishnan, Dives...
PODS
2006
ACM
134views Database» more  PODS 2006»
16 years 6 months ago
Approximate quantiles and the order of the stream
Recently, there has been an increased focus on modeling uncertainty by distributions. Suppose we wish to compute a function of a stream whose elements are samples drawn independen...
Sudipto Guha, Andrew McGregor
ICIAP
2005
ACM
16 years 6 months ago
A Neural Adaptive Algorithm for Feature Selection and Classification of High Dimensionality Data
In this paper, we propose a novel method which involves neural adaptive techniques for identifying salient features and for classifying high dimensionality data. In particular a ne...
Elisabetta Binaghi, Ignazio Gallo, Mirco Boschetti...
ICSE
2004
IEEE-ACM
16 years 6 months ago
A Framework for Ensuring and Improving Dependability in Highly Distributed Systems
A distributed software system's deployment architecture can have a significant impact on the system's dependability. Dependability is a function of various system paramet...
Sam Malek, Nels Beckman, Marija Mikic-Rakic, Nenad...
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