Distinguishing Two Probability Ensembles with One Sample from each Ensemble
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://repositorio.inesctec.pt/handle/123456789/7057 http://dx.doi.org/10.1007/s00224-015-9661-1 |
Resumo: | We introduced a new method for distinguishing two probability ensembles called one from each method, in which the distinguisher receives as input two samples, one from each ensemble. We compare this new method with multi-sample from the same method already exiting in the literature and prove that there are ensembles distinguishable by the new method, but indistinguishable by the multi-sample from the same method. To evaluate the power of the proposed method we also show that if non-uniform distinguishers (probabilistic circuits) are used, the one from each method is not more powerful than the classical one, in the sense that does not distinguish more probability ensembles. Moreover we obtain that there are classes of ensembles, such that any two members of the class are easily distinguishable (a definition introduced in this paper) using one sample from each ensemble; there are pairs of ensembles in the same class that are indistinguishable by multi-sample from the same method. |
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Distinguishing Two Probability Ensembles with One Sample from each EnsembleWe introduced a new method for distinguishing two probability ensembles called one from each method, in which the distinguisher receives as input two samples, one from each ensemble. We compare this new method with multi-sample from the same method already exiting in the literature and prove that there are ensembles distinguishable by the new method, but indistinguishable by the multi-sample from the same method. To evaluate the power of the proposed method we also show that if non-uniform distinguishers (probabilistic circuits) are used, the one from each method is not more powerful than the classical one, in the sense that does not distinguish more probability ensembles. Moreover we obtain that there are classes of ensembles, such that any two members of the class are easily distinguishable (a definition introduced in this paper) using one sample from each ensemble; there are pairs of ensembles in the same class that are indistinguishable by multi-sample from the same method.2018-01-19T10:40:09Z2016-01-01T00:00:00Z2016info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/7057http://dx.doi.org/10.1007/s00224-015-9661-1engLuís Filipe AntunesBuhrman,HMatos,ASouto,AAndreia Sofia Teixeirainfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-05-15T10:20:22Zoai:repositorio.inesctec.pt:123456789/7057Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:53:02.001569Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Distinguishing Two Probability Ensembles with One Sample from each Ensemble |
title |
Distinguishing Two Probability Ensembles with One Sample from each Ensemble |
spellingShingle |
Distinguishing Two Probability Ensembles with One Sample from each Ensemble Luís Filipe Antunes |
title_short |
Distinguishing Two Probability Ensembles with One Sample from each Ensemble |
title_full |
Distinguishing Two Probability Ensembles with One Sample from each Ensemble |
title_fullStr |
Distinguishing Two Probability Ensembles with One Sample from each Ensemble |
title_full_unstemmed |
Distinguishing Two Probability Ensembles with One Sample from each Ensemble |
title_sort |
Distinguishing Two Probability Ensembles with One Sample from each Ensemble |
author |
Luís Filipe Antunes |
author_facet |
Luís Filipe Antunes Buhrman,H Matos,A Souto,A Andreia Sofia Teixeira |
author_role |
author |
author2 |
Buhrman,H Matos,A Souto,A Andreia Sofia Teixeira |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Luís Filipe Antunes Buhrman,H Matos,A Souto,A Andreia Sofia Teixeira |
description |
We introduced a new method for distinguishing two probability ensembles called one from each method, in which the distinguisher receives as input two samples, one from each ensemble. We compare this new method with multi-sample from the same method already exiting in the literature and prove that there are ensembles distinguishable by the new method, but indistinguishable by the multi-sample from the same method. To evaluate the power of the proposed method we also show that if non-uniform distinguishers (probabilistic circuits) are used, the one from each method is not more powerful than the classical one, in the sense that does not distinguish more probability ensembles. Moreover we obtain that there are classes of ensembles, such that any two members of the class are easily distinguishable (a definition introduced in this paper) using one sample from each ensemble; there are pairs of ensembles in the same class that are indistinguishable by multi-sample from the same method. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-01-01T00:00:00Z 2016 2018-01-19T10:40:09Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://repositorio.inesctec.pt/handle/123456789/7057 http://dx.doi.org/10.1007/s00224-015-9661-1 |
url |
http://repositorio.inesctec.pt/handle/123456789/7057 http://dx.doi.org/10.1007/s00224-015-9661-1 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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