We show that for even quasi-concave objective functions the worst-case distribution, with respect to a family of unimodal distributions, of a stochastic programming problem is a u...
Objective Bayesian probability is often defined over rather simple domains, e.g., finite event spaces or propositional languages. This paper investigates the extension of objectiv...
This paper is focused on the evaluation of listening test that was realized with a view to objectively annotate expressive speech recordings and further develop a limited domain ex...
In this paper, we propose an energy functional to segment objects whose global shape is a priori known thanks to a statistical model. Our work aims at extending the variational ap...
Xavier Bresson, Pierre Vandergheynst, Jean-Philipp...
Abstract—A general variational framework for image approximation and segmentation is introduced. By using a continuous “line-process” to represent edge boundaries, it is poss...