Classification algorithms typically induce population-wide models that are trained to perform well on average on expected future instances. We introduce a Bayesian framework for l...
Biological systems are traditionally studied by focusing on a specific subsystem, building an intuitive model for it, and refining the model using results from carefully designed ...
Irit Gat-Viks, Amos Tanay, Daniela Raijman, Ron Sh...
: - Intrusion Detection Systems are increasingly a key part of systems defense. Various approaches to Intrusion Detection are currently being used, but they are relatively ineffect...
— The paper studies the observability properties of the relative localization of two Autonomous Underwater Vehicles (AUVs) equipped with depth sensors, linear/angular velocity se...
This paper studies the use of statistical induction techniques as a basis for automated performance diagnosis and performance management. The goal of the work is to develop and ev...
Ira Cohen, Jeffrey S. Chase, Julie Symons, Mois&ea...