Zobrazeno 1 - 10
of 77
pro vyhledávání: '"Gerson Zaverucha"'
Publikováno v:
PLoS Computational Biology, Vol 12, Iss 7, p e1005038 (2016)
Traditional protein annotation methods describe known domains with probabilistic models representing consensus among homologous domain sequences. However, when relevant signals become too weak to be identified by a global consensus, attempts for anno
Externí odkaz:
https://doaj.org/article/28e22b31588e4da29f8803d65c7a5886
Publikováno v:
Inductive Logic Programming ISBN: 9783030974534
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9e3473c119b40c0e2b52b1923d27a07a
https://doi.org/10.1007/978-3-030-97454-1_12
https://doi.org/10.1007/978-3-030-97454-1_12
Publikováno v:
Inductive Logic Programming ISBN: 9783030974534
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::17f57e2fb9ed505a0b3d9b070a8c594a
https://doi.org/10.1007/978-3-030-97454-1_9
https://doi.org/10.1007/978-3-030-97454-1_9
Autor:
Caina Figueiredo, Joao Gabriel Lopes, Rodrigo Azevedo, Daniel Vieira, Lucas Miranda, Gerson Zaverucha, Leandro Pfleger de Aguiar, Daniel Sadoc Menasche
Publikováno v:
IEEE Transactions on Network and Service Management. :1-1
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fae7ad5d7cc4f5b2f58b657d2a56b721
https://doi.org/10.1109/tnsm.2023.3234554
https://doi.org/10.1109/tnsm.2023.3234554
Autor:
Tarek R. Besold, Artur d’Avila Garcez, Sebastian Bader, Howard Bowman, Pedro Domingos, Pascal Hitzler, Kai-Uwe Kühnberger, Luis C. Lamb, Priscila Machado Vieira Lima, Leo de Penning, Gadi Pinkas, Hoifung Poon, Gerson Zaverucha
The study and understanding of human behaviour is relevant to computer science, artificial intelligence, neural computation, cognitive science, philosophy, psychology, and several other areas. Presupposing cognition as basis of behaviour, among the m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b8f994f9c5b14a295ac1a53d425a142f
https://doi.org/10.3233/faia210348
https://doi.org/10.3233/faia210348
Autor:
Joao Gabriel Lopes, Caina Figueiredo, Leandro Pfleger de Aguiar, Gerson Zaverucha, Rodrigo Azevedo, Daniel Sadoc Menasche
Publikováno v:
CSR
Data on software vulnerabilities, products and exploits is typically collected from multiple non-structured sources. Valuable information, e.g., on which products are affected by which exploits, is conveyed by matching data from those sources, i.e.,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d7a9633c9d20aad968508661951f22c1
https://doi.org/10.1109/csr51186.2021.9527984
https://doi.org/10.1109/csr51186.2021.9527984
Publikováno v:
Machine Learning. 108:1165-1189
Handling relational data streams has become a crucial task, given the availability of pervasive sensors and Internet-produced content, such as social networks and knowledge graphs. In a relational environment, this is a particularly challenging task,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::efa78d739830bae12c20f1a0a7da11ac
https://doi.org/10.1007/s10994-019-05798-y
https://doi.org/10.1007/s10994-019-05798-y
Publikováno v:
Anais do Concurso de Teses e Dissertações da SBC (CTD-SBC 2020).
Statistical machine learning algorithms usually assume that there is considerably-size data to train the models. However, they would fail in addressing domains where data is difficult or expensive to obtain. Transfer learning has emerged to address t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::913fe36345c3649bf9fbd6f394800232
https://doi.org/10.5753/ctd.2020.11371
https://doi.org/10.5753/ctd.2020.11371
Autor:
Tatiana Sciammarella, Gerson Zaverucha
Publikováno v:
Inductive Logic Programming ISBN: 9783030492090
ILP
ILP
Relational data models are usually used by researchers and companies when a single-table model is not enough to describe their system. Then, when it comes to classification, there are mainly two options: apply the corresponding relational version of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a195cf2daa9ed9eeb21ad09f6fb68723
https://doi.org/10.1007/978-3-030-49210-6_10
https://doi.org/10.1007/978-3-030-49210-6_10
Publikováno v:
Information Sciences. :108-124
Traditionally, algorithms that learn the structure of Bayesian Networks either start from an empty graph and add edges to it bit by bit or add/ remove/reverse edges in a randomly initialized graph. In both cases, the search space is constituted of al
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4a3c9902edf5a97ac53bc5a5c284da74
https://doi.org/10.1016/j.ins.2018.02.011
https://doi.org/10.1016/j.ins.2018.02.011