-June 1 2025, is the arrival date.
-Plenary Speakers:
Panos M. Pardalos, University of Florida, USA
Title: Dynamics of Information Systems
Abstract: TBA
Jose C. Principe, University of Florida, USA
Title: TBA
Abstract: TBA
R. Terry Rockafellar, University of Washington, USA
Title: Adapting Information to Different Quantifactions of Risk
Abstract: Information and entropy, going back in concept to Shannon in appraising how much can be learned from one probability distribution relative to another, is fundamental in Bayesian statistics and the classics of means and variances. But in application to a random loss, the distribution of which might be influenced by decision variables in a problem of optimization, the expectation is just risk-neutral. It’s best when circumstances where the loss is greater than expected will be balanced in the long run by instances where it is less. Many situations in finance and engineering, however, don’t include a long run, and the focus must then be on risk-averse appraisals. It has been found dangerous, for instance, to view the value of a stock just through historical mean and variance; properties of the tail distribution associated with losses, especially high losses, are more important than parts associated with gains. A broad theory has, for this reason, been developed about alternative quantifications of risk. A quantification that is averse and deemed coherent fits into a scheme which identifies a corresponding alternative for standard deviation and is able to trigger a tailored approach to regression beyond least-squares. Such quantifications have been shown moreover to be closedly tied to stochastic divergences beyond Kullbach-Leibler. This suggest perhaps defining information and entropy differently for each of them and exploring the many consequences.
Xin-She Yang, Middlesex University, UK
Title: Nature-Inspired algorithms for optimization
Abstract: TBA