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ISIPTA
2005
IEEE
155views Mathematics» more  ISIPTA 2005»
14 years 18 days ago
Estimation of Chaotic Probabilities
A Chaotic Probability model is a usual set of probability measures, M, the totality of which is endowed with an objective, frequentist interpretation as opposed to being viewed as...
Leandro Chaves Rêgo, Terrence L. Fine
IJAR
2010
105views more  IJAR 2010»
13 years 4 months ago
A tree augmented classifier based on Extreme Imprecise Dirichlet Model
In this paper we present TANC, i.e., a tree-augmented naive credal classifier based on imprecise probabilities; it models prior near-ignorance via the Extreme Imprecise Dirichlet ...
G. Corani, C. P. de Campos
ISIPTA
2003
IEEE
111views Mathematics» more  ISIPTA 2003»
14 years 8 days ago
Convex Imprecise Previsions: Basic Issues and Applications
In this paper we study two classes of imprecise previsions, which we termed convex and centered convex previsions, in the framework of Walley’s theory of imprecise previsions. W...
Renato Pelessoni, Paolo Vicig
IJAR
2010
91views more  IJAR 2010»
13 years 5 months ago
Inference and risk measurement with the pari-mutuel model
We explore generalizations of the pari-mutuel model (PMM), a formalization of an intuitive way of assessing an upper probability from a precise one. We discuss a naive extension o...
Renato Pelessoni, Paolo Vicig, Marco Zaffalon
IPMI
2007
Springer
14 years 7 months ago
Liver Segmentation Using Sparse 3D Prior Models with Optimal Data Support
Abstract. Volume segmentation is a relatively slow process and, in certain circumstances, the enormous amount of prior knowledge available is underused. Model-based liver segmentat...
Charles Florin, Nikos Paragios, Gareth Funka-Lea, ...