Recently there has been significant interest in employing probabilistic techniques for fault localization. Using dynamic dependence information for multiple passing runs, learnin...
We propose a new unsupervised learning technique for extracting information from large text collections. We model documents as if they were generated by a two-stage stochastic pro...
Mark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, T...
We formulate the problem of distributed throughput-efficient sensing in cognitive radio (CR) networks as a dynamic coalition formation game based on a Markovian model. The propose...
In this paper, we characterize the user behavior in a peer-to-peer (P2P) file sharing network. Our characterization is based on the results of an extensive passive measurement stu...
Alexander Klemm, Christoph Lindemann, Oliver P. Wa...
In implementations of non-standard database systems, large objects are often embedded within an aggregate of different types, i.e. a tuple. For a given size and access probabilit...