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Trabalho de evento
Modelling graph neural network by aggregating the activation maps of self-organizing map (2024)
Martins, Luan Vinicius de Carvalho ; Donghong, Ji; Liang, Zhao
Source: Proceedings. Conference titles: International Joint Conference on Neural Networks - IJCNN. Unidades: FFCLRP, ICMC
Subjects: REDES NEURAIS, TEORIA DOS GRAFOS
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ABNT
MARTINS, Luan Vinicius de Carvalho e DONGHONG, Ji e LIANG, Zhao. Modelling graph neural network by aggregating the activation maps of self-organizing map. 2024, Anais.. Piscataway: IEEE, 2024. Disponível em: https://doi.org/10.1109/IJCNN60899.2024.10650514. Acesso em: 01 nov. 2024.
APA
Martins, L. V. de C., Donghong, J., & Liang, Z. (2024). Modelling graph neural network by aggregating the activation maps of self-organizing map. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN60899.2024.10650514
NLM
Martins LV de C, Donghong J, Liang Z. Modelling graph neural network by aggregating the activation maps of self-organizing map [Internet]. Proceedings. 2024 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/IJCNN60899.2024.10650514
Vancouver
Martins LV de C, Donghong J, Liang Z. Modelling graph neural network by aggregating the activation maps of self-organizing map [Internet]. Proceedings. 2024 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/IJCNN60899.2024.10650514
Trabalho de evento
Portal NURC-SP: design, development, and speech processing corpora resources to support the public dissemination of portuguese spoken language (2024)
Rodrigues, Ana Carolina; Macedo, Alessandra Alaniz ; Candido Junior, Arnaldo ; Svartman, Flaviane Romani Fernandes ; Craveiro, Giovana Meloni; Leite, Marli Quadros ; Aluísio, Sandra Maria ; Santos, Vinícius Gonçalves dos ; Garcia, Vinícius Molina
Source: Proceedings. Conference titles: International Conference on Computational Processing of Portuguese - PROPOR. Unidades: FFCLRP, FFLCH, ICMC
Subjects: CORPUS, SÍNTESE DE FALA, PROSÓDIA, PORTUGUÊS DO BRASIL
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RODRIGUES, Ana Carolina et al. Portal NURC-SP: design, development, and speech processing corpora resources to support the public dissemination of portuguese spoken language. 2024, Anais.. Stroudsburg: ACL, 2024. Disponível em: https://aclanthology.org/2024.propor-1.19. Acesso em: 01 nov. 2024.
APA
Rodrigues, A. C., Macedo, A. A., Candido Junior, A., Svartman, F. R. F., Craveiro, G. M., Leite, M. Q., et al. (2024). Portal NURC-SP: design, development, and speech processing corpora resources to support the public dissemination of portuguese spoken language. In Proceedings. Stroudsburg: ACL. Recuperado de https://aclanthology.org/2024.propor-1.19
NLM
Rodrigues AC, Macedo AA, Candido Junior A, Svartman FRF, Craveiro GM, Leite MQ, Aluísio SM, Santos VG dos, Garcia VM. Portal NURC-SP: design, development, and speech processing corpora resources to support the public dissemination of portuguese spoken language [Internet]. Proceedings. 2024 ;[citado 2024 nov. 01 ] Available from: https://aclanthology.org/2024.propor-1.19
Vancouver
Rodrigues AC, Macedo AA, Candido Junior A, Svartman FRF, Craveiro GM, Leite MQ, Aluísio SM, Santos VG dos, Garcia VM. Portal NURC-SP: design, development, and speech processing corpora resources to support the public dissemination of portuguese spoken language [Internet]. Proceedings. 2024 ;[citado 2024 nov. 01 ] Available from: https://aclanthology.org/2024.propor-1.19
Trabalho de evento
TransGNN: a transductive graph neural network with graph dynamic embedding (2023)
Anghinoni, Leandro ; Yu-Tao, Zhu; Donghong, Ji; Liang, Zhao
Source: Proceedings. Conference titles: International Joint Conference on Neural Networks - IJCNN. Unidades: FFCLRP, ICMC
Subjects: APRENDIZADO COMPUTACIONAL, REDES NEURAIS
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ABNT
ANGHINONI, Leandro et al. TransGNN: a transductive graph neural network with graph dynamic embedding. 2023, Anais.. Piscataway: IEEE, 2023. Disponível em: https://doi.org/10.1109/IJCNN54540.2023.10191134. Acesso em: 01 nov. 2024.
APA
Anghinoni, L., Yu-Tao, Z., Donghong, J., & Liang, Z. (2023). TransGNN: a transductive graph neural network with graph dynamic embedding. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN54540.2023.10191134
NLM
Anghinoni L, Yu-Tao Z, Donghong J, Liang Z. TransGNN: a transductive graph neural network with graph dynamic embedding [Internet]. Proceedings. 2023 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/IJCNN54540.2023.10191134
Vancouver
Anghinoni L, Yu-Tao Z, Donghong J, Liang Z. TransGNN: a transductive graph neural network with graph dynamic embedding [Internet]. Proceedings. 2023 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/IJCNN54540.2023.10191134
Trabalho de evento
ITS Unplugged: leapfrogging the digital divide for teaching numeracy skills in underserved populations (2023)
Silva, Thomaz Edson Veloso da; Challco, Geiser Chalco ; Rodrigues, Luiz Antonio Lima ; Versuti, Fabiana Maris ; Penha, Rodolfo Sena da ; Oliveira, Lívia Silva; Guerino, Guilherme ; Amorin, Luis Felipe Cavalcanti de ; Marinho, Marcelo Luiz Monteiro ; Macario, Valmir ; Dermeval, Diego ; Pinto, Ig Ibert Bittencourt Santana ; Isotani, Seiji
Source: Proceedings. Conference titles: Workshop Towards the Future of AI-Augmented Human Tutoring in Math Learning. Unidades: FFCLRP, ICMC
Subjects: VISÃO COMPUTACIONAL, PROCESSAMENTO DE LINGUAGEM NATURAL, TOMADA DE DECISÃO
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ABNT
SILVA, Thomaz Edson Veloso da et al. ITS Unplugged: leapfrogging the digital divide for teaching numeracy skills in underserved populations. 2023, Anais.. Aache: CEUR-WS, 2023. Disponível em: https://ceur-ws.org/Vol-3491/paper6.pdf. Acesso em: 01 nov. 2024.
APA
Silva, T. E. V. da, Challco, G. C., Rodrigues, L. A. L., Versuti, F. M., Penha, R. S. da, Oliveira, L. S., et al. (2023). ITS Unplugged: leapfrogging the digital divide for teaching numeracy skills in underserved populations. In Proceedings. Aache: CEUR-WS. Recuperado de https://ceur-ws.org/Vol-3491/paper6.pdf
NLM
Silva TEV da, Challco GC, Rodrigues LAL, Versuti FM, Penha RS da, Oliveira LS, Guerino G, Amorin LFC de, Marinho MLM, Macario V, Dermeval D, Pinto IIBS, Isotani S. ITS Unplugged: leapfrogging the digital divide for teaching numeracy skills in underserved populations [Internet]. Proceedings. 2023 ;[citado 2024 nov. 01 ] Available from: https://ceur-ws.org/Vol-3491/paper6.pdf
Vancouver
Silva TEV da, Challco GC, Rodrigues LAL, Versuti FM, Penha RS da, Oliveira LS, Guerino G, Amorin LFC de, Marinho MLM, Macario V, Dermeval D, Pinto IIBS, Isotani S. ITS Unplugged: leapfrogging the digital divide for teaching numeracy skills in underserved populations [Internet]. Proceedings. 2023 ;[citado 2024 nov. 01 ] Available from: https://ceur-ws.org/Vol-3491/paper6.pdf
Trabalho de evento
WSI2ML: an open-source whole slide image annotation software for machine learning applications (2023)
Martins, Luan Vinicius de Carvalho ; Bueno, Adriana Passos ; Defelicibus, Alexandre ; Drummond, Rodrigo Duarte ; Valieris, Renan ; Yu-Tao, Zhu ; Silva, Israel Tojal da ; Liang, Zhao
Source: Proceedings. Conference titles: Brazilian Symposium on Multimedia and the Web - WebMedia. Unidades: FFCLRP, ICMC
Subjects: BIOINFORMÁTICA, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE IMAGEM, PATOLOGIA CLÍNICA, TECNOLOGIAS DA SAÚDE
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ABNT
MARTINS, Luan Vinicius de Carvalho et al. WSI2ML: an open-source whole slide image annotation software for machine learning applications. 2023, Anais.. New York: ACM, 2023. Disponível em: https://doi.org/10.1145/3617023.3617038. Acesso em: 01 nov. 2024.
APA
Martins, L. V. de C., Bueno, A. P., Defelicibus, A., Drummond, R. D., Valieris, R., Yu-Tao, Z., et al. (2023). WSI2ML: an open-source whole slide image annotation software for machine learning applications. In Proceedings. New York: ACM. doi:10.1145/3617023.3617038
NLM
Martins LV de C, Bueno AP, Defelicibus A, Drummond RD, Valieris R, Yu-Tao Z, Silva IT da, Liang Z. WSI2ML: an open-source whole slide image annotation software for machine learning applications [Internet]. Proceedings. 2023 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1145/3617023.3617038
Vancouver
Martins LV de C, Bueno AP, Defelicibus A, Drummond RD, Valieris R, Yu-Tao Z, Silva IT da, Liang Z. WSI2ML: an open-source whole slide image annotation software for machine learning applications [Internet]. Proceedings. 2023 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1145/3617023.3617038
Trabalho de evento
Feature selection using complex networks to support price trend forecast in energy markets (2023)
Castilho, Douglas; Santos, Moises Rocha dos ; Tinós, Renato ; Carvalho, André Carlos Ponce de Leon Ferreira de ; Paula, Marcos Basile Saviano de; Ladeira, Lucas; Guarnier, Ewerton ; Silva Filho, Donato ; Suiama, Danilo Y; Macedo Junior, Edmur A; Alipio, Lucas P
Source: Proceedings. Conference titles: International Joint Conference on Neural Networks - IJCNN. Unidades: FFCLRP, ICMC
Subjects: REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL, PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS), ENERGIA ELÉTRICA
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ABNT
CASTILHO, Douglas et al. Feature selection using complex networks to support price trend forecast in energy markets. 2023, Anais.. Piscataway: IEEE, 2023. Disponível em: https://doi.org/10.1109/IJCNN54540.2023.10191426. Acesso em: 01 nov. 2024.
APA
Castilho, D., Santos, M. R. dos, Tinós, R., Carvalho, A. C. P. de L. F. de, Paula, M. B. S. de, Ladeira, L., et al. (2023). Feature selection using complex networks to support price trend forecast in energy markets. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN54540.2023.10191426
NLM
Castilho D, Santos MR dos, Tinós R, Carvalho ACP de LF de, Paula MBS de, Ladeira L, Guarnier E, Silva Filho D, Suiama DY, Macedo Junior EA, Alipio LP. Feature selection using complex networks to support price trend forecast in energy markets [Internet]. Proceedings. 2023 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/IJCNN54540.2023.10191426
Vancouver
Castilho D, Santos MR dos, Tinós R, Carvalho ACP de LF de, Paula MBS de, Ladeira L, Guarnier E, Silva Filho D, Suiama DY, Macedo Junior EA, Alipio LP. Feature selection using complex networks to support price trend forecast in energy markets [Internet]. Proceedings. 2023 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/IJCNN54540.2023.10191426
Trabalho de evento
Complex network-based data classification using minimum spanning tree metric and optimization (2023)
Saire, Josimar Edinson Chire ; Liang, Zhao
Source: Proceedings. Conference titles: International Joint Conference on Neural Networks - IJCNN. Unidades: FFCLRP, ICMC
Subjects: REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL
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ABNT
SAIRE, Josimar Edinson Chire e LIANG, Zhao. Complex network-based data classification using minimum spanning tree metric and optimization. 2023, Anais.. Piscataway: IEEE, 2023. Disponível em: https://doi.org/10.1109/IJCNN54540.2023.10191004. Acesso em: 01 nov. 2024.
APA
Saire, J. E. C., & Liang, Z. (2023). Complex network-based data classification using minimum spanning tree metric and optimization. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN54540.2023.10191004
NLM
Saire JEC, Liang Z. Complex network-based data classification using minimum spanning tree metric and optimization [Internet]. Proceedings. 2023 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/IJCNN54540.2023.10191004
Vancouver
Saire JEC, Liang Z. Complex network-based data classification using minimum spanning tree metric and optimization [Internet]. Proceedings. 2023 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/IJCNN54540.2023.10191004
Trabalho de evento-anais periodico
Maximizing portfolio profitability during a cryptocurrency downtrend: a bitcoin blockchain transaction-based approach (2023)
Zuñiga, Esteban Wilfredo Vilca ; Ranieri, Caetano Mazzoni ; Zhao, Liang ; Ueyama, Jó ; Zhu, Yu-tao; Ji, Donghong
Source: Proceedings. Conference titles: International Neural Network Society Workshop on Deep Learning Innovations and Applications - INNS DLIA. Unidades: FFCLRP, ICMC
Subjects: DINHEIRO ELETRÔNICO, APRENDIZAGEM PROFUNDA, REDES COMPLEXAS, INVESTIMENTOS, LUCRO
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ABNT
ZUÑIGA, Esteban Wilfredo Vilca et al. Maximizing portfolio profitability during a cryptocurrency downtrend: a bitcoin blockchain transaction-based approach. Proceedings. Amsterdam: Elsevier. Disponível em: https://doi.org/10.1016/j.procs.2023.08.192. Acesso em: 01 nov. 2024. , 2023
APA
Zuñiga, E. W. V., Ranieri, C. M., Zhao, L., Ueyama, J., Zhu, Y. -tao, & Ji, D. (2023). Maximizing portfolio profitability during a cryptocurrency downtrend: a bitcoin blockchain transaction-based approach. Proceedings. Amsterdam: Elsevier. doi:10.1016/j.procs.2023.08.192
NLM
Zuñiga EWV, Ranieri CM, Zhao L, Ueyama J, Zhu Y-tao, Ji D. Maximizing portfolio profitability during a cryptocurrency downtrend: a bitcoin blockchain transaction-based approach [Internet]. Proceedings. 2023 ; 222 539-548.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1016/j.procs.2023.08.192
Vancouver
Zuñiga EWV, Ranieri CM, Zhao L, Ueyama J, Zhu Y-tao, Ji D. Maximizing portfolio profitability during a cryptocurrency downtrend: a bitcoin blockchain transaction-based approach [Internet]. Proceedings. 2023 ; 222 539-548.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1016/j.procs.2023.08.192
Trabalho de evento
Machine learning approach for trend prediction to improve returns on brazilian energy market (2022)
Santos, Moises Rocha dos ; Braz, Douglas Donizeti de Castilho; Carvalho, André Carlos Ponce de Leon Ferreira de ; Tinós, Renato ; Paula, Marcos Basile Saviano de; Doretto, Gabriel; Guarnier, Ewerton ; Silva Filho, Donato ; Suiama, Danilo Y; Ferreira, Lorena E; Carmo Junior, José E
Source: Proceedings. Conference titles: IEEE Latin American Conference on Computational Intelligence - LA-CCI. Unidades: ICMC, FFCLRP
Subjects: APRENDIZADO COMPUTACIONAL, PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS), ENERGIA ELÉTRICA, POLÍTICA DE PREÇO
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ABNT
SANTOS, Moises Rocha dos et al. Machine learning approach for trend prediction to improve returns on brazilian energy market. 2022, Anais.. Los Alamitos: IEEE, 2022. Disponível em: https://doi.org/10.1109/LA-CCI54402.2022.9981846. Acesso em: 01 nov. 2024.
APA
Santos, M. R. dos, Braz, D. D. de C., Carvalho, A. C. P. de L. F. de, Tinós, R., Paula, M. B. S. de, Doretto, G., et al. (2022). Machine learning approach for trend prediction to improve returns on brazilian energy market. In Proceedings. Los Alamitos: IEEE. doi:10.1109/LA-CCI54402.2022.9981846
NLM
Santos MR dos, Braz DD de C, Carvalho ACP de LF de, Tinós R, Paula MBS de, Doretto G, Guarnier E, Silva Filho D, Suiama DY, Ferreira LE, Carmo Junior JE. Machine learning approach for trend prediction to improve returns on brazilian energy market [Internet]. Proceedings. 2022 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/LA-CCI54402.2022.9981846
Vancouver
Santos MR dos, Braz DD de C, Carvalho ACP de LF de, Tinós R, Paula MBS de, Doretto G, Guarnier E, Silva Filho D, Suiama DY, Ferreira LE, Carmo Junior JE. Machine learning approach for trend prediction to improve returns on brazilian energy market [Internet]. Proceedings. 2022 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/LA-CCI54402.2022.9981846
Trabalho de evento
An optimized modularity-based high level classification model (2020)
Colliri, Tiago Santos ; Weiguang, Liu; Liang, Zhao
Source: Proceedings. Conference titles: International Joint Conference on Neural Networks - IJCNN. Unidades: FFCLRP, ICMC
Subjects: REDES COMPLEXAS, RECONHECIMENTO DE PADRÕES
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ABNT
COLLIRI, Tiago Santos e WEIGUANG, Liu e LIANG, Zhao. An optimized modularity-based high level classification model. 2020, Anais.. Piscataway: IEEE, 2020. Disponível em: https://doi.org/10.1109/IJCNN48605.2020.9206755. Acesso em: 01 nov. 2024.
APA
Colliri, T. S., Weiguang, L., & Liang, Z. (2020). An optimized modularity-based high level classification model. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN48605.2020.9206755
NLM
Colliri TS, Weiguang L, Liang Z. An optimized modularity-based high level classification model [Internet]. Proceedings. 2020 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/IJCNN48605.2020.9206755
Vancouver
Colliri TS, Weiguang L, Liang Z. An optimized modularity-based high level classification model [Internet]. Proceedings. 2020 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/IJCNN48605.2020.9206755
Trabalho de evento
Echo state network performance analysis using non-random topologies (2020)
Arroyo, Diana Carolina Roca ; Florez, Alexander Ylnner Choquenaira ; Flores, Daniela Milón ; Romero, Roseli Aparecida Francelin ; Liang, Zhao
Source: Proceedings. Conference titles: IEEE Colombian Conference on Applications of Computational Intelligence - ColCACI. Unidades: ICMC, FFCLRP
Subjects: SISTEMAS DINÂMICOS, ANÁLISE DE SÉRIES TEMPORAIS, REDES COMPLEXAS
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ABNT
ARROYO, Diana Carolina Roca et al. Echo state network performance analysis using non-random topologies. 2020, Anais.. Danvers: IEEE, 2020. Disponível em: https://doi.org/10.1109/ColCACI50549.2020.9248714. Acesso em: 01 nov. 2024.
APA
Arroyo, D. C. R., Florez, A. Y. C., Flores, D. M., Romero, R. A. F., & Liang, Z. (2020). Echo state network performance analysis using non-random topologies. In Proceedings. Danvers: IEEE. doi:10.1109/ColCACI50549.2020.9248714
NLM
Arroyo DCR, Florez AYC, Flores DM, Romero RAF, Liang Z. Echo state network performance analysis using non-random topologies [Internet]. Proceedings. 2020 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/ColCACI50549.2020.9248714
Vancouver
Arroyo DCR, Florez AYC, Flores DM, Romero RAF, Liang Z. Echo state network performance analysis using non-random topologies [Internet]. Proceedings. 2020 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/ColCACI50549.2020.9248714
Trabalho de evento
Visualization to assist interpretation of the multilevel paradigm in bipartite graphs (2020)
Cintra, Diego Silva ; Valejo, Alan Demetrius Baria ; Lopes, Alneu de Andrade ; Oliveira, Maria Cristina Ferreira de
Source: Proceedings. Conference titles: International joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - VISIGRAPP. Unidades: ICMC, FFCLRP
Subjects: VISUALIZAÇÃO, COMPUTAÇÃO GRÁFICA
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ABNT
CINTRA, Diego Silva et al. Visualization to assist interpretation of the multilevel paradigm in bipartite graphs. 2020, Anais.. Lisboa: SciTePress, 2020. Disponível em: https://doi.org/10.5220/0008903501330140. Acesso em: 01 nov. 2024.
APA
Cintra, D. S., Valejo, A. D. B., Lopes, A. de A., & Oliveira, M. C. F. de. (2020). Visualization to assist interpretation of the multilevel paradigm in bipartite graphs. In Proceedings. Lisboa: SciTePress. doi:10.5220/0008903501330140
NLM
Cintra DS, Valejo ADB, Lopes A de A, Oliveira MCF de. Visualization to assist interpretation of the multilevel paradigm in bipartite graphs [Internet]. Proceedings. 2020 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.5220/0008903501330140
Vancouver
Cintra DS, Valejo ADB, Lopes A de A, Oliveira MCF de. Visualization to assist interpretation of the multilevel paradigm in bipartite graphs [Internet]. Proceedings. 2020 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.5220/0008903501330140
Trabalho de evento
Particle competition for multilayer network community detection (2019)
Gao, Xubo; Zheng, Qiusheng; Verri, Filipe Alves Neto ; Rodrigues, Rafael Delalibera ; Liang, Zhao
Source: Proceedings. Conference titles: International Conference on Machine Learning and Computing - ICMLC. Unidades: FFCLRP, ICMC
Subjects: TEORIA DA COMPUTAÇÃO, ALGORITMOS, APRENDIZADO COMPUTACIONAL
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ABNT
GAO, Xubo et al. Particle competition for multilayer network community detection. 2019, Anais.. New York: ACM, 2019. Disponível em: https://doi.org/10.1145/3318299.3318320. Acesso em: 01 nov. 2024.
APA
Gao, X., Zheng, Q., Verri, F. A. N., Rodrigues, R. D., & Liang, Z. (2019). Particle competition for multilayer network community detection. In Proceedings. New York: ACM. doi:10.1145/3318299.3318320
NLM
Gao X, Zheng Q, Verri FAN, Rodrigues RD, Liang Z. Particle competition for multilayer network community detection [Internet]. Proceedings. 2019 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1145/3318299.3318320
Vancouver
Gao X, Zheng Q, Verri FAN, Rodrigues RD, Liang Z. Particle competition for multilayer network community detection [Internet]. Proceedings. 2019 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1145/3318299.3318320
Trabalho de evento
A network-based model for optimizing returns in the stock market (2019)
Colliri, Tiago Santos ; Liang, Zhao
Source: Proceedings. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidades: FFCLRP, ICMC
Subjects: REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL, BOLSA DE VALORES
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ABNT
COLLIRI, Tiago Santos e LIANG, Zhao. A network-based model for optimizing returns in the stock market. 2019, Anais.. Piscataway: IEEE, 2019. Disponível em: https://doi.org/10.1109/BRACIS.2019.00118. Acesso em: 01 nov. 2024.
APA
Colliri, T. S., & Liang, Z. (2019). A network-based model for optimizing returns in the stock market. In Proceedings. Piscataway: IEEE. doi:10.1109/BRACIS.2019.00118
NLM
Colliri TS, Liang Z. A network-based model for optimizing returns in the stock market [Internet]. Proceedings. 2019 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/BRACIS.2019.00118
Vancouver
Colliri TS, Liang Z. A network-based model for optimizing returns in the stock market [Internet]. Proceedings. 2019 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/BRACIS.2019.00118
Trabalho de evento-anais periodico
Feature learning in feature–sample networks using multi-objective optimization (2018)
Verri, Filipe Alves Neto ; Tinós, Renato ; Liang, Zhao
Source: Proceedings. Conference titles: IEEE Congress on Evolutionary Computation - CEC. Unidades: FFCLRP, ICMC
Subjects: CIÊNCIA DA COMPUTAÇÃO, REDES DE COMPUTADORES, ALGORITMOS GENÉTICOS
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ABNT
VERRI, Filipe Alves Neto e TINÓS, Renato e LIANG, Zhao. Feature learning in feature–sample networks using multi-objective optimization. Proceedings. Piscataway: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. Disponível em: https://doi.org/10.1109/CEC.2018.8477891. Acesso em: 01 nov. 2024. , 2018
APA
Verri, F. A. N., Tinós, R., & Liang, Z. (2018). Feature learning in feature–sample networks using multi-objective optimization. Proceedings. Piscataway: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. doi:10.1109/CEC.2018.8477891
NLM
Verri FAN, Tinós R, Liang Z. Feature learning in feature–sample networks using multi-objective optimization [Internet]. Proceedings. 2018 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/CEC.2018.8477891
Vancouver
Verri FAN, Tinós R, Liang Z. Feature learning in feature–sample networks using multi-objective optimization [Internet]. Proceedings. 2018 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/CEC.2018.8477891
Trabalho de evento
Improving semantic role labeling using high-level classification in complex networks (2017)
Carneiro, Murilo G; Rosa, João Luís Garcia ; Qiusheng, Zheng; Xiaoming, Liu; Liang, Zhao
Source: Proceedings. Conference titles: International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery - ICNC-FSKD. Unidades: ICMC, FFCLRP
Subjects: REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE PADRÕES
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ABNT
CARNEIRO, Murilo G et al. Improving semantic role labeling using high-level classification in complex networks. 2017, Anais.. Los Alamitos: IEEE, 2017. Disponível em: https://doi.org/10.1109/FSKD.2017.8393113. Acesso em: 01 nov. 2024.
APA
Carneiro, M. G., Rosa, J. L. G., Qiusheng, Z., Xiaoming, L., & Liang, Z. (2017). Improving semantic role labeling using high-level classification in complex networks. In Proceedings. Los Alamitos: IEEE. doi:10.1109/FSKD.2017.8393113
NLM
Carneiro MG, Rosa JLG, Qiusheng Z, Xiaoming L, Liang Z. Improving semantic role labeling using high-level classification in complex networks [Internet]. Proceedings. 2017 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/FSKD.2017.8393113
Vancouver
Carneiro MG, Rosa JLG, Qiusheng Z, Xiaoming L, Liang Z. Improving semantic role labeling using high-level classification in complex networks [Internet]. Proceedings. 2017 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/FSKD.2017.8393113
Trabalho de evento
Graph-based semi-supervised learning for semantic role diffusion (2016)
Carneiro, M. G; Liang, Zhao; Rosa, João Luís Garcia
Source: Proceedings. Conference titles: Symposium on Knowledge Discovery, Mining and Learning - KDMiLe. Unidades: FFCLRP, ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL, PROCESSAMENTO DE LINGUAGEM NATURAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CARNEIRO, M. G e LIANG, Zhao e ROSA, João Luís Garcia. Graph-based semi-supervised learning for semantic role diffusion. 2016, Anais.. Porto Alegre: SBC, 2016. . Acesso em: 01 nov. 2024.
APA
Carneiro, M. G., Liang, Z., & Rosa, J. L. G. (2016). Graph-based semi-supervised learning for semantic role diffusion. In Proceedings. Porto Alegre: SBC.
NLM
Carneiro MG, Liang Z, Rosa JLG. Graph-based semi-supervised learning for semantic role diffusion. Proceedings. 2016 ;[citado 2024 nov. 01 ]
Vancouver
Carneiro MG, Liang Z, Rosa JLG. Graph-based semi-supervised learning for semantic role diffusion. Proceedings. 2016 ;[citado 2024 nov. 01 ]
Trabalho de evento
An object-based visual selection model combining physical features and memory (2014)
Benicasa, Alcides X; Quiles, Marcos G; Silva, Thiago C; Liang, Zhao; Romero, Roseli Aparecida Francelin
Source: Proceedings. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidades: FFCLRP, ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, RECONHECIMENTO DE PADRÕES, VISÃO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BENICASA, Alcides X et al. An object-based visual selection model combining physical features and memory. 2014, Anais.. Los Alamitos: Conference Publishing Services, 2014. Disponível em: https://doi.org/10.1109/BRACIS.2014.50. Acesso em: 01 nov. 2024.
APA
Benicasa, A. X., Quiles, M. G., Silva, T. C., Liang, Z., & Romero, R. A. F. (2014). An object-based visual selection model combining physical features and memory. In Proceedings. Los Alamitos: Conference Publishing Services. doi:10.1109/BRACIS.2014.50
NLM
Benicasa AX, Quiles MG, Silva TC, Liang Z, Romero RAF. An object-based visual selection model combining physical features and memory [Internet]. Proceedings. 2014 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/BRACIS.2014.50
Vancouver
Benicasa AX, Quiles MG, Silva TC, Liang Z, Romero RAF. An object-based visual selection model combining physical features and memory [Internet]. Proceedings. 2014 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/BRACIS.2014.50
Trabalho de evento
A flocking-like technique to perform semi-supervised learning (2014)
Gueleri, Roberto A; Cupertino, Thiago H; Carvalho, André Carlos Ponce de Leon Ferreira de ; Liang, Zhao
Source: Proceedings. Conference titles: International Joint Conference on Neural Networks - IJCNN. Unidades: ICMC, FFCLRP
Subjects: INTELIGÊNCIA ARTIFICIAL, REDES NEURAIS, COMPUTAÇÃO BIOINSPIRADA, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GUELERI, Roberto A et al. A flocking-like technique to perform semi-supervised learning. 2014, Anais.. Piscataway: IEEE, 2014. Disponível em: https://doi.org/10.1109/IJCNN.2014.6889434. Acesso em: 01 nov. 2024.
APA
Gueleri, R. A., Cupertino, T. H., Carvalho, A. C. P. de L. F. de, & Liang, Z. (2014). A flocking-like technique to perform semi-supervised learning. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN.2014.6889434
NLM
Gueleri RA, Cupertino TH, Carvalho ACP de LF de, Liang Z. A flocking-like technique to perform semi-supervised learning [Internet]. Proceedings. 2014 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/IJCNN.2014.6889434
Vancouver
Gueleri RA, Cupertino TH, Carvalho ACP de LF de, Liang Z. A flocking-like technique to perform semi-supervised learning [Internet]. Proceedings. 2014 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/IJCNN.2014.6889434
Trabalho de evento
Proposta de um cubo de dados para imagens médicas baseado em similaridade (2010)
Annibal, Luana Peixoto; Ciferri, Ricardo Rodrigues (Orientador); Felipe, Joaquim Cezar (coorient); Ciferri, Cristina Dutra de Aguiar (colab)
Source: Proceedings. Conference titles: Brazilian Symposium on Databases. Unidades: ICMC, FFCLRP
Subjects: BANCO DE DADOS, COMPUTAÇÃO GRÁFICA, PROCESSAMENTO DE IMAGENS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ANNIBAL, Luana Peixoto. Proposta de um cubo de dados para imagens médicas baseado em similaridade. 2010, Anais.. Porto Alegre: SBC, 2010. . Acesso em: 01 nov. 2024.
APA
Annibal, L. P. (2010). Proposta de um cubo de dados para imagens médicas baseado em similaridade. In Proceedings. Porto Alegre: SBC.
NLM
Annibal LP. Proposta de um cubo de dados para imagens médicas baseado em similaridade. Proceedings. 2010 ;[citado 2024 nov. 01 ]
Vancouver
Annibal LP. Proposta de um cubo de dados para imagens médicas baseado em similaridade. Proceedings. 2010 ;[citado 2024 nov. 01 ]

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