We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
In this paper we study the problem of bounding the value of the probability distribution function of a random variable X at E[X] + a where a is a small quantity in comparison with...
Sensor positioning is a crucial part of many location-dependent applications that utilize wireless sensor networks (WSNs). Current localization approaches can be divided into two ...
Different solvers for computationally difficult problems such as satisfiability (SAT) perform best on different instances. Algorithm portfolios exploit this phenomenon by predicti...
Models of language learning play a central role in a wide range of applications: from psycholinguistic theories of how people acquire new word knowledge, to information systems th...