Data streaming systems are becoming essential for monitoring applications such as financial analysis and network intrusion detection. These systems often have to process many simi...
Sailesh Krishnamurthy, Chung Wu, Michael J. Frankl...
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...
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...
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...
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...