We consider the problem of approximating sliding window joins over data streams in a data stream processing system with limited resources. In our model, we deal with resource cons...
We study the problem of estimating selectivity of approximate substring queries. Its importance in databases is ever increasing as more and more data are input by users and are in...
Abstract. Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of th...
— Approximating the sum of Log–Normal random variables (RVs) is a long–standing open issue, in the old and recent literature, and many approaches have been proposed to deal w...
Marco Di Renzo, Fabio Graziosi, Fortunato Santucci
We consider the problem of private efficient data mining of vertically-partitioned databases. Each of several parties holds a column of a data matrix (a vector) and the parties wan...
Yuval Ishai, Tal Malkin, Martin J. Strauss, Rebecc...