We present a probabilistic analysis of integer linear programs (ILPs). More specifically, we study ILPs in a so-called smoothed analysis in which it is assumed that first an adve...
Interpretation for Worst and Average Case Analysis Alessandra Di Pierro1 , Chris Hankin2 , and Herbert Wiklicky2 1 Dipartimento di Informatica, University of Pisa, Italy 2 Departme...
Alessandra Di Pierro, Chris Hankin, Herbert Wiklic...
MayBMS is a state-of-the-art probabilistic database management system which leverages the strengths of previous database research for achieving scalability. As a proof of concept ...
Jiewen Huang, Lyublena Antova, Christoph Koch, Dan...
We present further developments in our work on using data from real users to build a probabilistic model of user affect based on Dynamic Bayesian Networks (DBNs) and designed to de...
Automation of power system fault identification using information conveyed by the wavelet analysis of power system transients is proposed. Probabilistic Neural Network (PNN) for d...