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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Kuznetsov independence for interval-valued expectations and sets of probability distributions: Properties and algorithms

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Autor(es):
Cozman, Fabio G. [1] ; de Campos, Cassio Polpo [2]
Número total de Autores: 2
Afiliação do(s) autor(es):
[1] Univ Sao Paulo, Sao Paulo - Brazil
[2] Ist Dalle Molle Studi Intelligenza Artificiale ID, CH-6928 Manno - Switzerland
Número total de Afiliações: 2
Tipo de documento: Artigo Científico
Fonte: INTERNATIONAL JOURNAL OF APPROXIMATE REASONING; v. 55, n. 2, p. 666-682, JAN 2014.
Citações Web of Science: 7
Resumo

Kuznetsov independence of variables X and Y means that, for any pair of bounded functions f(X) and g(Y), E{[}f(X)g(Y)] = E{[}f(X)] boxed times E{[}g(Y)], where IE{[}.] denotes interval-valued expectation and boxed times denotes interval multiplication. We present properties of Kuznetsov independence for several variables, and connect it with other concepts of independence in the literature; in particular we show that strong extensions are always included in sets of probability distributions whose lower and upper expectations satisfy Kuznetsov independence. We introduce an algorithm that computes lower expectations subject to judgments of Kuznetsov independence by mixing column generation techniques with nonlinear programming. Finally, we define a concept of conditional Kuznetsov independence, and study its graphoid properties. (C) 2013 Elsevier Inc. All rights reserved. (AU)

Processo FAPESP: 04/09568-0 - Algoritmos para inferência e aprendizado para lógica probabilística com relações de independência
Beneficiário:Fabio Gagliardi Cozman
Linha de fomento: Auxílio à Pesquisa - Regular