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Artigo de periodico
Keywords attention for fake news detection using few positive labels (2024)
Souza, Mariana Caravanti de ; Gôlo, Marcos Paulo Silva ; Jorge, Alípio Mário Guedes ; Amorim, Evelin Carvalho Freire de ; Campos, Ricardo Nuno Taborda; Marcacini, Ricardo Marcondes ; Rezende, Solange Oliveira
Fonte: Information Sciences. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, FAKE NEWS
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ABNT
SOUZA, Mariana Caravanti de et al. Keywords attention for fake news detection using few positive labels. Information Sciences, v. 663, p. 1-23, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.ins.2024.120300. Acesso em: 01 ago. 2024.
APA
Souza, M. C. de, Gôlo, M. P. S., Jorge, A. M. G., Amorim, E. C. F. de, Campos, R. N. T., Marcacini, R. M., & Rezende, S. O. (2024). Keywords attention for fake news detection using few positive labels. Information Sciences, 663, 1-23. doi:10.1016/j.ins.2024.120300
NLM
Souza MC de, Gôlo MPS, Jorge AMG, Amorim ECF de, Campos RNT, Marcacini RM, Rezende SO. Keywords attention for fake news detection using few positive labels [Internet]. Information Sciences. 2024 ; 663 1-23.[citado 2024 ago. 01 ] Available from: https://doi.org/10.1016/j.ins.2024.120300
Vancouver
Souza MC de, Gôlo MPS, Jorge AMG, Amorim ECF de, Campos RNT, Marcacini RM, Rezende SO. Keywords attention for fake news detection using few positive labels [Internet]. Information Sciences. 2024 ; 663 1-23.[citado 2024 ago. 01 ] Available from: https://doi.org/10.1016/j.ins.2024.120300
Artigo de periodico
Unsupervised heterogeneous graph neural networks for one-class tasks: exploring early fusion operators (2024)
Gôlo, Marcos Paulo Silva ; Moraes Junior, Marcelo Isaias de ; Goularte, Rudinei ; Marcacini, Ricardo Marcondes
Fonte: Journal on Interactive Systems. Unidade: ICMC
Assuntos: REDES NEURAIS, TEORIA DOS GRAFOS
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ABNT
GÔLO, Marcos Paulo Silva et al. Unsupervised heterogeneous graph neural networks for one-class tasks: exploring early fusion operators. Journal on Interactive Systems, v. 15, n. 1, p. 517-529, 2024Tradução . . Disponível em: https://doi.org/10.5753/jis.2024.4109. Acesso em: 01 ago. 2024.
APA
Gôlo, M. P. S., Moraes Junior, M. I. de, Goularte, R., & Marcacini, R. M. (2024). Unsupervised heterogeneous graph neural networks for one-class tasks: exploring early fusion operators. Journal on Interactive Systems, 15( 1), 517-529. doi:10.5753/jis.2024.4109
NLM
Gôlo MPS, Moraes Junior MI de, Goularte R, Marcacini RM. Unsupervised heterogeneous graph neural networks for one-class tasks: exploring early fusion operators [Internet]. Journal on Interactive Systems. 2024 ; 15( 1): 517-529.[citado 2024 ago. 01 ] Available from: https://doi.org/10.5753/jis.2024.4109
Vancouver
Gôlo MPS, Moraes Junior MI de, Goularte R, Marcacini RM. Unsupervised heterogeneous graph neural networks for one-class tasks: exploring early fusion operators [Internet]. Journal on Interactive Systems. 2024 ; 15( 1): 517-529.[citado 2024 ago. 01 ] Available from: https://doi.org/10.5753/jis.2024.4109
Trabalho de evento
BioAutoML: democratizing machine learning in life sciences (2024)
Bonidia, Robson Parmezan ; Carvalho, Andre Carlos Ponce de Leon Ferreira de
Fonte: Anais estendidos. Nome do evento: Simpósio Brasileiro de Computação Aplicada à Saúde - SBCAS. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, BIOINFORMÁTICA, GENÔMICA
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ABNT
BONIDIA, Robson Parmezan e CARVALHO, Andre Carlos Ponce de Leon Ferreira de. BioAutoML: democratizing machine learning in life sciences. 2024, Anais.. Porto Alegre: SBC, 2024. Disponível em: https://doi.org/10.5753/sbcas_estendido.2024.2184. Acesso em: 01 ago. 2024.
APA
Bonidia, R. P., & Carvalho, A. C. P. de L. F. de. (2024). BioAutoML: democratizing machine learning in life sciences. In Anais estendidos. Porto Alegre: SBC. doi:10.5753/sbcas_estendido.2024.2184
NLM
Bonidia RP, Carvalho ACP de LF de. BioAutoML: democratizing machine learning in life sciences [Internet]. Anais estendidos. 2024 ;[citado 2024 ago. 01 ] Available from: https://doi.org/10.5753/sbcas_estendido.2024.2184
Vancouver
Bonidia RP, Carvalho ACP de LF de. BioAutoML: democratizing machine learning in life sciences [Internet]. Anais estendidos. 2024 ;[citado 2024 ago. 01 ] Available from: https://doi.org/10.5753/sbcas_estendido.2024.2184
Artigo de periodico
The impact of representation learning on unsupervised graph neural networks for one-class recommendation (2024)
Gôlo, Marcos Paulo Silva ; Moraes, Leonardo Gonçalves de ; Goularte, Rudinei ; Marcacini, Ricardo Marcondes
Fonte: Journal of Information and Data Management - JIDM. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, SISTEMAS DE RECOMENDAÇÃO, REDES NEURAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GÔLO, Marcos Paulo Silva et al. The impact of representation learning on unsupervised graph neural networks for one-class recommendation. Journal of Information and Data Management - JIDM, v. 15, n. 1, p. 112-122, 2024Tradução . . Disponível em: https://doi.org/10.5753/jidm.2024.3317. Acesso em: 01 ago. 2024.
APA
Gôlo, M. P. S., Moraes, L. G. de, Goularte, R., & Marcacini, R. M. (2024). The impact of representation learning on unsupervised graph neural networks for one-class recommendation. Journal of Information and Data Management - JIDM, 15( 1), 112-122. doi:10.5753/jidm.2024.3317
NLM
Gôlo MPS, Moraes LG de, Goularte R, Marcacini RM. The impact of representation learning on unsupervised graph neural networks for one-class recommendation [Internet]. Journal of Information and Data Management - JIDM. 2024 ; 15( 1): 112-122.[citado 2024 ago. 01 ] Available from: https://doi.org/10.5753/jidm.2024.3317
Vancouver
Gôlo MPS, Moraes LG de, Goularte R, Marcacini RM. The impact of representation learning on unsupervised graph neural networks for one-class recommendation [Internet]. Journal of Information and Data Management - JIDM. 2024 ; 15( 1): 112-122.[citado 2024 ago. 01 ] Available from: https://doi.org/10.5753/jidm.2024.3317
Trabalho de evento
On the use of early fusion operators on heterogeneous graph neural networks for one-class learning (2023)
Gôlo, Marcos Paulo Silva ; Moraes Junior, Marcelo Isaias de ; Goularte, Rudinei ; Marcacini, Ricardo Marcondes
Fonte: Proceedings. Nome do evento: Brazilian Symposium on Multimedia and the Web - WebMedia. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, REDES NEURAIS, MULTIMÍDIA INTERATIVA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GÔLO, Marcos Paulo Silva et al. On the use of early fusion operators on heterogeneous graph neural networks for one-class learning. 2023, Anais.. New York: ACM, 2023. Disponível em: https://doi.org/10.1145/3617023.3617041. Acesso em: 01 ago. 2024.
APA
Gôlo, M. P. S., Moraes Junior, M. I. de, Goularte, R., & Marcacini, R. M. (2023). On the use of early fusion operators on heterogeneous graph neural networks for one-class learning. In Proceedings. New York: ACM. doi:10.1145/3617023.3617041
NLM
Gôlo MPS, Moraes Junior MI de, Goularte R, Marcacini RM. On the use of early fusion operators on heterogeneous graph neural networks for one-class learning [Internet]. Proceedings. 2023 ;[citado 2024 ago. 01 ] Available from: https://doi.org/10.1145/3617023.3617041
Vancouver
Gôlo MPS, Moraes Junior MI de, Goularte R, Marcacini RM. On the use of early fusion operators on heterogeneous graph neural networks for one-class learning [Internet]. Proceedings. 2023 ;[citado 2024 ago. 01 ] Available from: https://doi.org/10.1145/3617023.3617041
Artigo de periodico
Spatial index structures for modern storage devices: a survey (2023)
Carniel, Anderson Chaves ; Aguiar, Cristina Dutra de
Fonte: IEEE Transactions on Knowledge and Data Engineering. Unidade: ICMC
Assuntos: BANCO DE DADOS, SISTEMA DE INFORMAÇÃO GEOGRÁFICA, RECUPERAÇÃO DA INFORMAÇÃO
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ABNT
CARNIEL, Anderson Chaves e AGUIAR, Cristina Dutra de. Spatial index structures for modern storage devices: a survey. IEEE Transactions on Knowledge and Data Engineering, v. 35, n. 9, p. 9578-9597, 2023Tradução . . Disponível em: https://doi.org/10.1109/TKDE.2023.3242207. Acesso em: 01 ago. 2024.
APA
Carniel, A. C., & Aguiar, C. D. de. (2023). Spatial index structures for modern storage devices: a survey. IEEE Transactions on Knowledge and Data Engineering, 35( 9), 9578-9597. doi:10.1109/TKDE.2023.3242207
NLM
Carniel AC, Aguiar CD de. Spatial index structures for modern storage devices: a survey [Internet]. IEEE Transactions on Knowledge and Data Engineering. 2023 ; 35( 9): 9578-9597.[citado 2024 ago. 01 ] Available from: https://doi.org/10.1109/TKDE.2023.3242207
Vancouver
Carniel AC, Aguiar CD de. Spatial index structures for modern storage devices: a survey [Internet]. IEEE Transactions on Knowledge and Data Engineering. 2023 ; 35( 9): 9578-9597.[citado 2024 ago. 01 ] Available from: https://doi.org/10.1109/TKDE.2023.3242207
Trabalho de evento-anais periodico
Open science in the cloud: the CloudFAIR architecture for FAIR-compliant repositories (2022)
Castro, João Pedro de Carvalho ; Romero, Lucas de Medeiros França ; Carniel, Anderson Chaves ; Aguiar, Cristina Dutra de
Fonte: Communications in Computer and Information Science. Nome do evento: European Conference on Advances in Databases and Information Systems - ADBIS. Unidade: ICMC
Assuntos: COMPUTAÇÃO EM NUVEM, ARQUITETURA DE SOFTWARE
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ABNT
CASTRO, João Pedro de Carvalho et al. Open science in the cloud: the CloudFAIR architecture for FAIR-compliant repositories. Communications in Computer and Information Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-15743-1_6. Acesso em: 01 ago. 2024. , 2022
APA
Castro, J. P. de C., Romero, L. de M. F., Carniel, A. C., & Aguiar, C. D. de. (2022). Open science in the cloud: the CloudFAIR architecture for FAIR-compliant repositories. Communications in Computer and Information Science. Cham: Springer. doi:10.1007/978-3-031-15743-1_6
NLM
Castro JP de C, Romero L de MF, Carniel AC, Aguiar CD de. Open science in the cloud: the CloudFAIR architecture for FAIR-compliant repositories [Internet]. Communications in Computer and Information Science. 2022 ; 1652 56-66.[citado 2024 ago. 01 ] Available from: https://doi.org/10.1007/978-3-031-15743-1_6
Vancouver
Castro JP de C, Romero L de MF, Carniel AC, Aguiar CD de. Open science in the cloud: the CloudFAIR architecture for FAIR-compliant repositories [Internet]. Communications in Computer and Information Science. 2022 ; 1652 56-66.[citado 2024 ago. 01 ] Available from: https://doi.org/10.1007/978-3-031-15743-1_6
Trabalho de evento-anais periodico
Lessons learned from the NeurIPS 2021 MetaDL challenge: backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification (2022)
Baz, Adrian El; Ullah, Ihsan; Alcobaça, Edesio ; Carvalho, André Carlos Ponce de Leon Ferreira de ; Chen, Hong; Ferreira, Fábio; Gouk, Henry; Guan, Chaoyu; Guyon, Isabelle; Hospedales, Timothy; Hu, Shell; Huisman, Mike ; Hutter, Frank ; Liu, Zhengying; Mohr, Felix ; Öztürk, Ekrem ; Rijn, Jan N. van ; Sun, Haozhe; Wang, Xin; Zhu, Wenwu
Fonte: Proceedings of Machine Learning Research : PMLR. Nome do evento: Conference on Neural Information Processing Systems - NeurIPS. Unidade: ICMC
Assunto: APRENDIZADO COMPUTACIONAL
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ABNT
BAZ, Adrian El et al. Lessons learned from the NeurIPS 2021 MetaDL challenge: backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification. Proceedings of Machine Learning Research : PMLR. Brookline: Microtome Publishing. Disponível em: https://proceedings.mlr.press/v176/el-baz22a.html. Acesso em: 01 ago. 2024. , 2022
APA
Baz, A. E., Ullah, I., Alcobaça, E., Carvalho, A. C. P. de L. F. de, Chen, H., Ferreira, F., et al. (2022). Lessons learned from the NeurIPS 2021 MetaDL challenge: backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification. Proceedings of Machine Learning Research : PMLR. Brookline: Microtome Publishing. Recuperado de https://proceedings.mlr.press/v176/el-baz22a.html
NLM
Baz AE, Ullah I, Alcobaça E, Carvalho ACP de LF de, Chen H, Ferreira F, Gouk H, Guan C, Guyon I, Hospedales T, Hu S, Huisman M, Hutter F, Liu Z, Mohr F, Öztürk E, Rijn JN van, Sun H, Wang X, Zhu W. Lessons learned from the NeurIPS 2021 MetaDL challenge: backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification [Internet]. Proceedings of Machine Learning Research : PMLR. 2022 ; 176 80-96.[citado 2024 ago. 01 ] Available from: https://proceedings.mlr.press/v176/el-baz22a.html
Vancouver
Baz AE, Ullah I, Alcobaça E, Carvalho ACP de LF de, Chen H, Ferreira F, Gouk H, Guan C, Guyon I, Hospedales T, Hu S, Huisman M, Hutter F, Liu Z, Mohr F, Öztürk E, Rijn JN van, Sun H, Wang X, Zhu W. Lessons learned from the NeurIPS 2021 MetaDL challenge: backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification [Internet]. Proceedings of Machine Learning Research : PMLR. 2022 ; 176 80-96.[citado 2024 ago. 01 ] Available from: https://proceedings.mlr.press/v176/el-baz22a.html
Trabalho de evento-anais periodico
Storing feature vectors in relational image data warehouses (2022)
Rocha, Guilherme Muzzi da ; Capelo, Piero Lima ; Carniel, Anderson Chaves ; Aguiar, Cristina Dutra de
Fonte: Communications in Computer and Information Science. Nome do evento: European Conference on Advances in Databases and Information Systems - ADBIS. Unidade: ICMC
Assuntos: BANCO DE DADOS MULTIMÍDIA, RECUPERAÇÃO DA INFORMAÇÃO, RECONHECIMENTO DE IMAGEM
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ROCHA, Guilherme Muzzi da et al. Storing feature vectors in relational image data warehouses. Communications in Computer and Information Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-15743-1_30. Acesso em: 01 ago. 2024. , 2022
APA
Rocha, G. M. da, Capelo, P. L., Carniel, A. C., & Aguiar, C. D. de. (2022). Storing feature vectors in relational image data warehouses. Communications in Computer and Information Science. Cham: Springer. doi:10.1007/978-3-031-15743-1_30
NLM
Rocha GM da, Capelo PL, Carniel AC, Aguiar CD de. Storing feature vectors in relational image data warehouses [Internet]. Communications in Computer and Information Science. 2022 ; 1652 323-331.[citado 2024 ago. 01 ] Available from: https://doi.org/10.1007/978-3-031-15743-1_30
Vancouver
Rocha GM da, Capelo PL, Carniel AC, Aguiar CD de. Storing feature vectors in relational image data warehouses [Internet]. Communications in Computer and Information Science. 2022 ; 1652 323-331.[citado 2024 ago. 01 ] Available from: https://doi.org/10.1007/978-3-031-15743-1_30

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