Walley’s Imprecise Dirichlet Model (IDM) for categorical data overcomes several fundamental problems which other approaches to uncertainty suffer from. Yet, to be useful in prac...
Abstract--This paper focuses on the way to achieve accurate visual servoing tasks when the shape of the object being observed as well as the desired image are unknown. More precise...
This paper proposes a robust estimation and validation framework for characterizing local structures in a positive multi-variate continuous function approximated by a Gaussian-base...
Nonparametric methods are widely applicable to statistical learning problems, since they rely on a few modeling assumptions. In this context, the fresh look advocated here permeat...
In a reverberant scenario, phase transformed weighted algorithms are more robust than Maximum Likelihood (ML) because of the insufficiency of the data model to incorporate reverb...