Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Thiago de Paulo Faleiros"'
Publikováno v:
Applied Network Science, Vol 8, Iss 1, Pp 1-21 (2023)
Abstract The growing data size poses challenges for storage and computational processing time in semi-supervised models, making their practical application difficult; researchers have explored the use of reduced network versions as a potential soluti
Externí odkaz:
https://doaj.org/article/94799f75fe934f4abb5f515985438e1d
Autor:
Thiago de Paulo Faleiros
Publikováno v:
Biblioteca Digital de Teses e Dissertações da USPUniversidade de São PauloUSP.
Tratar grandes quantidades de dados é uma exigência dos modernos algoritmos de mineração de texto. Para algumas aplicações, documentos são constantemente publicados, o que demanda alto custo de armazenamento em longo prazo. Então, é necessá
Publikováno v:
Anais do XIX Encontro Nacional de Inteligência Artificial e Computacional (ENIAC 2022).
Neste trabalho, pretende-se aplicar os modelos de tópicos e avaliar os resultados a fim de se obter informações relacionandos os assuntos dos discursos dos senadores ao longo do tempo. O contexto atual da sociedade é marcado por um excesso de inf
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5ada99fc3ddbfdbef83c97e9e2cd2fd0
https://doi.org/10.5753/eniac.2022.227634
https://doi.org/10.5753/eniac.2022.227634
Publikováno v:
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Universidade de São Paulo (USP)
instacron:USP
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6752aa89b404a670eb9fcc451fed02c8
https://doi.org/10.3233/ida-194528
https://doi.org/10.3233/ida-194528
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031248658
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::afd51e6123b4f00781c4ca8bc5a62634
https://doi.org/10.1007/978-3-031-24866-5_21
https://doi.org/10.1007/978-3-031-24866-5_21
Autor:
Paulo Eduardo Althoff, Liang Zhao, Weiguang Liu, Thiago de Paulo Faleiros, Alan Valejo, Jianglong Yan, Maria Lígia Chuerubim
Publikováno v:
Intelligent Systems ISBN: 9783030917012
Several coarsening algorithms have been developed as a powerful strategy to deal with difficult machine learning problems represented by large-scale networks, including, network visualization, trajectory mining, community detection and dimension redu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::da4e51a2174e8f584ba7c958e3913300
https://doi.org/10.1007/978-3-030-91702-9_29
https://doi.org/10.1007/978-3-030-91702-9_29
Publikováno v:
Intelligent Systems ISBN: 9783030916985
Deep learning models have been the state-of-the-art for a variety of challenging tasks in natural language processing, but to achieve good results they often require big labeled datasets. Deep active learning algorithms were designed to reduce the an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fa368272cad9359f6a895cca2b599ea8
https://doi.org/10.1007/978-3-030-91699-2_28
https://doi.org/10.1007/978-3-030-91699-2_28
Publikováno v:
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Universidade de São Paulo (USP)
instacron:USP
Scalable algorithm based on bipartite graphs to perform transduction learning.Label propagation procedure that uses class information associated with vertices and edges.Better performance than state-of-the-art algorithms based on vector space or grap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5c48696c109ff9b8e64b833bc8d09737
https://doi.org/10.1016/j.patrec.2016.04.006
https://doi.org/10.1016/j.patrec.2016.04.006
Publikováno v:
ICMLA
Many of the criminal cases analysed by the Prosecution Office of the Federal District and Territories are repetitive and processing them can be streamlined by providing similar previous cases as template. We investigate the use of information retriev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c7116ae8688adc366f9e1ecd9683e544
https://doi.org/10.1109/icmla.2019.00123
https://doi.org/10.1109/icmla.2019.00123
Autor:
Maria Cristina Ferreira de Oliveira, Alneu de Andrade Lopes, Alan Valejo, Thiago de Paulo Faleiros
Publikováno v:
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Universidade de São Paulo (USP)
instacron:USP
A multilevel method is a scalable strategy to solve optimization problems in large bipartite networks, which operates in three stages. Initially the input network is iteratively coarsened into a hierarchy of gradually smaller networks. Coarsening imp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9868c55da12d31f4795dcc987179f275
https://doi.org/10.1016/j.knosys.2020.105678
https://doi.org/10.1016/j.knosys.2020.105678