We consider here the case where our knowledge is partial and based on a betting density function which is n-dimensional Gaussian. The explicit formulation of the least committed b...
Francois Caron, Branko Ristic, Emmanuel Duflos, Ph...
Although financial risk measurement is a largely investigated research area, its relationship with imprecise probabilities has been mostly overlooked. However, risk measures can b...
Credal networks are models that extend Bayesian nets to deal with imprecision in probability, and can actually be regarded as sets of Bayesian nets. Credal nets appear to be power...
Empirical evidence shows that naive Bayesian classifiers perform quite well compared to more sophisticated network classifiers, even in view of inaccuracies in their parameters. I...
There exist many tools for capturing imprecision in probabilistic representations. Among them are random sets, possibility distributions, probability intervals, and the more recen...
The task of estimating causal effects from non-experimental data is notoriously difficult and unreliable. Nevertheless, precisely such estimates are commonly required in many fiel...
Patrik O. Hoyer, Shohei Shimizu, Antti J. Kerminen...
Abstract. There exist several simple representations of uncertainty that are easier to handle than more general ones. Among them are random sets, possibility distributions, probabi...
Portfolio management in finance is more than a mathematical problem of optimizing performance under risk constraints. A critical factor in practical portfolio problems is severe u...
Daniel Berleant, L. Andrieu, Jean-Philippe Argaud,...