We represent switching activity in VLSI circuits using a graphical probabilistic model based on Cascaded Bayesian Networks (CBN’s). We develop an elegant method for maintaining ...
Time series data is common in many settings including scientific and financial applications. In these applications, the amount of data is often very large. We seek to support pred...
Most data mining algorithms assume static behavior of the incoming data. In the real world, the situation is different and most continuously collected data streams are generated by...
Lior Cohen, Gil Avrahami, Mark Last, Abraham Kande...
In recent years, the proliferation of VOIP data has created a number of applications in which it is desirable to perform quick online classification and recognition of massive voi...
A common approach for dealing with large data sets is to stream over the input in one pass, and perform computations using sublinear resources. For truly massive data sets, howeve...
Jon Feldman, S. Muthukrishnan, Anastasios Sidiropo...