Abstract. Compositional reasoning aims to improve scalability of verification tools by reducing the original verification task into subproblems. The simplification is typically bas...
In recent years there has been a flurry of works on learning Bayesian networks from data. One of the hard problems in this area is how to effectively learn the structure of a beli...
We show a close relationship between the Expectation - Maximization (EM) algorithm and direct optimization algorithms such as gradientbased methods for parameter learning. We iden...
Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahra...
— We consider the problem of multiple mobile sensor agents tracking the position of one or more moving targets. In our formulation, each agent maintains a target estimate, and ea...
Abstract. Mainstream surrogate approaches for multi-objective problems build one approximation for each objective. Mono-surrogate approaches instead aim at characterizing the Paret...