In practice, learning from data is often hampered by the limited training examples. In this paper, as the size of training data varies, we empirically investigate several probabil...
We present an approximate analytical method to compute efficiently the call blocking probabilities in wavelength routing networks with multiple classes of calls. The model is fairl...
Sridhar Ramesh, George N. Rouskas, Harry G. Perros
This paper presents a query evaluation technique for positive relational algebra queries with aggregates on a representation system for probabilistic data based on the algebraic s...
We present a framework for approximating random-walk based probability distributions over Web pages using graph aggregation. We (1) partition the Web's graph into classes of ...
Andrei Z. Broder, Ronny Lempel, Farzin Maghoul, Ja...
Sources of data uncertainty and imprecision are numerous. A way to handle this uncertainty is to associate probabilistic annotations to data. Many such probabilistic database mode...