The use of the statistical technique of mixture model analysis as a tool for early prediction of fault-prone program modules is investigated. The Expectation-Maximum likelihood (E...
This paper concerns learning and prediction with probabilistic models where the domain sizes of latent variables have no a priori upper-bound. Current approaches represent prior d...
This paper is concerned with solar driven sensors deployed in an outdoor environment. We present feedback controllers which adapt parameters of the application such that a maximal...
Clemens Moser, Lothar Thiele, Davide Brunelli, Luc...
This paper assesses the predictability of network traffic by considering two metrics: (1) how far into the future a traffic rate process can be predicted with bounded error; (2) w...
— Providing approximate max-min fair bandwidth allocation among flows within a network or at a single router has been an important research problem. In this paper, we study the ...
Abhimanyu Das, Debojyoti Dutta, Ahmed Helmy, Ashis...