Robust Bayesian inference is the calculation of posterior probability bounds given perturbations in a probabilistic model. This paper focuses on perturbations that can be expresse...
We describe a novel inference algorithm for sparse Bayesian PCA with a zero-norm prior on the model parameters. Bayesian inference is very challenging in probabilistic models of t...
Calling context enhances program understanding and dynamic analyses by providing a rich representation of program location. Compared to imperative programs, objectoriented program...
Reciprocity is a pervasive concept that plays an important role in governing people’s behavior, judgments, and thus their social interactions. In this paper we present an analys...
We consider the timed automata model of [3], which allows the analysis of realtime systems expressed in terms of quantitative timing constraints. Traditional approaches to real-ti...
Marta Z. Kwiatkowska, Gethin Norman, Roberto Segal...