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Filtros : "Liang, Zhao" "ICMC" Removidos: "PROCESSAMENTO DE IMAGENS" "Financiamento CAPES" "Biometrical Journal" Limpar

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  • 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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      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: 30 ago. 2024.

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      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

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      Saire JEC, Liang Z. Complex network-based data classification using minimum spanning tree metric and optimization [Internet]. Proceedings. 2023 ;[citado 2024 ago. 30 ] 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 ago. 30 ] Available from: https://doi.org/10.1109/IJCNN54540.2023.10191004

  • 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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      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: 30 ago. 2024.

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      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

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      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 ago. 30 ] 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 ago. 30 ] Available from: https://doi.org/10.1145/3617023.3617038

  • Artigo de periodico

    Characterizing data patterns with core-periphery network modeling (2023)

    Jianglong, Yan; Anghinoni, Leandro ; Yu-Tao, Zhu; Weiguang, Liu; Gen, Li; Qiusheng, Zheng; Liang, Zhao

    Source: Journal of Computational Science. Unidades: FFCLRP, ICMC

    Subjects: REDES COMPLEXAS, RECONHECIMENTO DE IMAGEM, RADIOGRAFIA, COVID-19

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      JIANGLONG, Yan et al. Characterizing data patterns with core-periphery network modeling. Journal of Computational Science, v. 66, n. Ja 2023, p. 1-13, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.jocs.2022.101912. Acesso em: 30 ago. 2024.

    • APA

      Jianglong, Y., Anghinoni, L., Yu-Tao, Z., Weiguang, L., Gen, L., Qiusheng, Z., & Liang, Z. (2023). Characterizing data patterns with core-periphery network modeling. Journal of Computational Science, 66( Ja 2023), 1-13. doi:10.1016/j.jocs.2022.101912

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      Jianglong Y, Anghinoni L, Yu-Tao Z, Weiguang L, Gen L, Qiusheng Z, Liang Z. Characterizing data patterns with core-periphery network modeling [Internet]. Journal of Computational Science. 2023 ; 66( Ja 2023): 1-13.[citado 2024 ago. 30 ] Available from: https://doi.org/10.1016/j.jocs.2022.101912

    • Vancouver

      Jianglong Y, Anghinoni L, Yu-Tao Z, Weiguang L, Gen L, Qiusheng Z, Liang Z. Characterizing data patterns with core-periphery network modeling [Internet]. Journal of Computational Science. 2023 ; 66( Ja 2023): 1-13.[citado 2024 ago. 30 ] Available from: https://doi.org/10.1016/j.jocs.2022.101912

  • Artigo de periodico

    Network community detection via iterative edge removal in a flocking-like system (2021)

    Verri, Filipe Alves Neto ; Gueleri, Roberto Alves ; Qiusheng, Zheng; Junbao, Zhang; Liang, Zhao

    Source: European Physical Journal - Special Topics. Unidades: FFCLRP, ICMC

    Subjects: REDES COMPLEXAS, SISTEMAS DINÂMICOS, ALGORITMOS ÚTEIS E ESPECÍFICOS

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      VERRI, Filipe Alves Neto et al. Network community detection via iterative edge removal in a flocking-like system. European Physical Journal - Special Topics, v. 230, n. 14-15, p. 2843-2855, 2021Tradução . . Disponível em: https://doi.org/10.1140/epjs/s11734-021-00154-5. Acesso em: 30 ago. 2024.

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      Verri, F. A. N., Gueleri, R. A., Qiusheng, Z., Junbao, Z., & Liang, Z. (2021). Network community detection via iterative edge removal in a flocking-like system. European Physical Journal - Special Topics, 230( 14-15), 2843-2855. doi:10.1140/epjs/s11734-021-00154-5

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      Verri FAN, Gueleri RA, Qiusheng Z, Junbao Z, Liang Z. Network community detection via iterative edge removal in a flocking-like system [Internet]. European Physical Journal - Special Topics. 2021 ; 230( 14-15): 2843-2855.[citado 2024 ago. 30 ] Available from: https://doi.org/10.1140/epjs/s11734-021-00154-5

    • Vancouver

      Verri FAN, Gueleri RA, Qiusheng Z, Junbao Z, Liang Z. Network community detection via iterative edge removal in a flocking-like system [Internet]. European Physical Journal - Special Topics. 2021 ; 230( 14-15): 2843-2855.[citado 2024 ago. 30 ] Available from: https://doi.org/10.1140/epjs/s11734-021-00154-5

  • Artigo de periodico

    Time series pattern identification by hierarchical community detection (2021)

    Anghinoni, Leandro ; Vega-Oliveros, Didier Augusto ; Silva, Thiago Christiano ; Liang, Zhao

    Source: European Physical Journal - Special Topics. Unidades: FFCLRP, ICMC

    Subjects: REDES COMPLEXAS, ANÁLISE DE SÉRIES TEMPORAIS, RECONHECIMENTO DE PADRÕES

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      ANGHINONI, Leandro et al. Time series pattern identification by hierarchical community detection. European Physical Journal - Special Topics, v. 230, n. 14-15, p. 2775-2782, 2021Tradução . . Disponível em: https://doi.org/10.1140/epjs/s11734-021-00163-4. Acesso em: 30 ago. 2024.

    • APA

      Anghinoni, L., Vega-Oliveros, D. A., Silva, T. C., & Liang, Z. (2021). Time series pattern identification by hierarchical community detection. European Physical Journal - Special Topics, 230( 14-15), 2775-2782. doi:10.1140/epjs/s11734-021-00163-4

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      Anghinoni L, Vega-Oliveros DA, Silva TC, Liang Z. Time series pattern identification by hierarchical community detection [Internet]. European Physical Journal - Special Topics. 2021 ; 230( 14-15): 2775-2782.[citado 2024 ago. 30 ] Available from: https://doi.org/10.1140/epjs/s11734-021-00163-4

    • Vancouver

      Anghinoni L, Vega-Oliveros DA, Silva TC, Liang Z. Time series pattern identification by hierarchical community detection [Internet]. European Physical Journal - Special Topics. 2021 ; 230( 14-15): 2775-2782.[citado 2024 ago. 30 ] Available from: https://doi.org/10.1140/epjs/s11734-021-00163-4

  • Artigo de periodico

    Stock market trend detection and automatic decision-making through a network-based classification model (2021)

    Colliri, Tiago Santos ; Liang, Zhao

    Source: Natural Computing. Unidades: FFCLRP, ICMC

    Subjects: REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE PADRÕES, BOLSA DE VALORES

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      COLLIRI, Tiago Santos e LIANG, Zhao. Stock market trend detection and automatic decision-making through a network-based classification model. Natural Computing, v. 20, n. 4, p. 791-804, 2021Tradução . . Disponível em: https://doi.org/10.1007/s11047-020-09829-9. Acesso em: 30 ago. 2024.

    • APA

      Colliri, T. S., & Liang, Z. (2021). Stock market trend detection and automatic decision-making through a network-based classification model. Natural Computing, 20( 4), 791-804. doi:10.1007/s11047-020-09829-9

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      Colliri TS, Liang Z. Stock market trend detection and automatic decision-making through a network-based classification model [Internet]. Natural Computing. 2021 ; 20( 4): 791-804.[citado 2024 ago. 30 ] Available from: https://doi.org/10.1007/s11047-020-09829-9

    • Vancouver

      Colliri TS, Liang Z. Stock market trend detection and automatic decision-making through a network-based classification model [Internet]. Natural Computing. 2021 ; 20( 4): 791-804.[citado 2024 ago. 30 ] Available from: https://doi.org/10.1007/s11047-020-09829-9

  • Tese (Doutorado)

    Network-based high level classification: novel models and applications (2021)

    Colliri, Tiago Santos; Liang, Zhao (Orientador)

    Unidade: ICMC

    Subjects: REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL, COVID-19

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      COLLIRI, Tiago Santos. Network-based high level classification: novel models and applications. 2021. Tese (Doutorado) – Universidade de São Paulo, São Carlos, 2021. Disponível em: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-26032021-102400/. Acesso em: 30 ago. 2024.

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      Colliri, T. S. (2021). Network-based high level classification: novel models and applications (Tese (Doutorado). Universidade de São Paulo, São Carlos. Recuperado de https://www.teses.usp.br/teses/disponiveis/55/55134/tde-26032021-102400/

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      Colliri TS. Network-based high level classification: novel models and applications [Internet]. 2021 ;[citado 2024 ago. 30 ] Available from: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-26032021-102400/

    • Vancouver

      Colliri TS. Network-based high level classification: novel models and applications [Internet]. 2021 ;[citado 2024 ago. 30 ] Available from: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-26032021-102400/

  • 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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      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: 30 ago. 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

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      Colliri TS, Weiguang L, Liang Z. An optimized modularity-based high level classification model [Internet]. Proceedings. 2020 ;[citado 2024 ago. 30 ] 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 ago. 30 ] Available from: https://doi.org/10.1109/IJCNN48605.2020.9206755

  • Artigo de periodico

    A tourist walk approach for internal and external outlier detection (2020)

    Rodrigues, Rafael Delalibera ; Liang, Zhao ; Zheng, Qiusheng; Zhang, Junbao

    Source: Neurocomputing. Unidades: FFCLRP, ICMC

    Subjects: TURISMO, MEMÓRIA (ELETRÔNICA DIGITAL), ATRATORES

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      RODRIGUES, Rafael Delalibera et al. A tourist walk approach for internal and external outlier detection. Neurocomputing, v. 393, p. 203-213, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2018.10.113. Acesso em: 30 ago. 2024.

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      Rodrigues, R. D., Liang, Z., Zheng, Q., & Zhang, J. (2020). A tourist walk approach for internal and external outlier detection. Neurocomputing, 393, 203-213. doi:10.1016/j.neucom.2018.10.113

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      Rodrigues RD, Liang Z, Zheng Q, Zhang J. A tourist walk approach for internal and external outlier detection [Internet]. Neurocomputing. 2020 ; 393 203-213.[citado 2024 ago. 30 ] Available from: https://doi.org/10.1016/j.neucom.2018.10.113

    • Vancouver

      Rodrigues RD, Liang Z, Zheng Q, Zhang J. A tourist walk approach for internal and external outlier detection [Internet]. Neurocomputing. 2020 ; 393 203-213.[citado 2024 ago. 30 ] Available from: https://doi.org/10.1016/j.neucom.2018.10.113

  • Dissertação (Mestrado)

    A Two-Stage Particle Competition Model for Unbalanced Community Detection in Complex Networks (2020)

    Martins, Luan Vinicius de Carvalho; Liang, Zhao (Orientador)

    Unidade: ICMC

    Subjects: REDES COMPLEXAS, DINÂMICA ESTOCÁSTICA, COMPUTAÇÃO BIOINSPIRADA

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      MARTINS, Luan Vinicius de Carvalho. A Two-Stage Particle Competition Model for Unbalanced Community Detection in Complex Networks. 2020. Dissertação (Mestrado) – Universidade de São Paulo, São Carlos, 2020. Disponível em: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-20082020-101929/. Acesso em: 30 ago. 2024.

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      Martins, L. V. de C. (2020). A Two-Stage Particle Competition Model for Unbalanced Community Detection in Complex Networks (Dissertação (Mestrado). Universidade de São Paulo, São Carlos. Recuperado de https://www.teses.usp.br/teses/disponiveis/55/55134/tde-20082020-101929/

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      Martins LV de C. A Two-Stage Particle Competition Model for Unbalanced Community Detection in Complex Networks [Internet]. 2020 ;[citado 2024 ago. 30 ] Available from: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-20082020-101929/

    • Vancouver

      Martins LV de C. A Two-Stage Particle Competition Model for Unbalanced Community Detection in Complex Networks [Internet]. 2020 ;[citado 2024 ago. 30 ] Available from: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-20082020-101929/

  • Trabalho de evento-anais periodico

    Particle competition for unbalanced community detection in complex networks (2020)

    Martins, Luan Vinicius Carvalho; Liang, Zhao

    Source: Lecture Notes in Artificial Intelligence. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidades: FFCLRP, ICMC

    Assunto: REDES COMPLEXAS

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      MARTINS, Luan Vinicius Carvalho e LIANG, Zhao. Particle competition for unbalanced community detection in complex networks. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-61380-8_22. Acesso em: 30 ago. 2024. , 2020

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      Martins, L. V. C., & Liang, Z. (2020). Particle competition for unbalanced community detection in complex networks. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-030-61380-8_22

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      Martins LVC, Liang Z. Particle competition for unbalanced community detection in complex networks [Internet]. Lecture Notes in Artificial Intelligence. 2020 ; 12320 322-336.[citado 2024 ago. 30 ] Available from: https://doi.org/10.1007/978-3-030-61380-8_22

    • Vancouver

      Martins LVC, Liang Z. Particle competition for unbalanced community detection in complex networks [Internet]. Lecture Notes in Artificial Intelligence. 2020 ; 12320 322-336.[citado 2024 ago. 30 ] Available from: https://doi.org/10.1007/978-3-030-61380-8_22

  • Artigo de periodico

    Temporal network pattern identification by community modelling (2020)

    Gao, Xubo; Zheng, Qiusheng; Vega-Oliveros, Didier Augusto ; Anghinoni, Leandro ; Liang, Zhao

    Source: Scientific Reports. Unidades: FFCLRP, ICMC

    Subjects: MINERAÇÃO DE DADOS, ANÁLISE DE SÉRIES TEMPORAIS, RECONHECIMENTO DE PADRÕES

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      GAO, Xubo et al. Temporal network pattern identification by community modelling. Scientific Reports, v. 10, p. 1-12, 2020Tradução . . Disponível em: https://doi.org/10.1038/s41598-019-57123-1. Acesso em: 30 ago. 2024.

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      Gao, X., Zheng, Q., Vega-Oliveros, D. A., Anghinoni, L., & Liang, Z. (2020). Temporal network pattern identification by community modelling. Scientific Reports, 10, 1-12. doi:10.1038/s41598-019-57123-1

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      Gao X, Zheng Q, Vega-Oliveros DA, Anghinoni L, Liang Z. Temporal network pattern identification by community modelling [Internet]. Scientific Reports. 2020 ; 10 1-12.[citado 2024 ago. 30 ] Available from: https://doi.org/10.1038/s41598-019-57123-1

    • Vancouver

      Gao X, Zheng Q, Vega-Oliveros DA, Anghinoni L, Liang Z. Temporal network pattern identification by community modelling [Internet]. Scientific Reports. 2020 ; 10 1-12.[citado 2024 ago. 30 ] Available from: https://doi.org/10.1038/s41598-019-57123-1

  • 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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      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: 30 ago. 2024.

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      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

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      Arroyo DCR, Florez AYC, Flores DM, Romero RAF, Liang Z. Echo state network performance analysis using non-random topologies [Internet]. Proceedings. 2020 ;[citado 2024 ago. 30 ] 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 ago. 30 ] Available from: https://doi.org/10.1109/ColCACI50549.2020.9248714

  • Trabalho de evento-anais periodico

    Predicting the evolution of COVID-19 cases and deaths through a correlations-based temporal network (2020)

    Colliri, Tiago Santos ; Delbem, Alexandre Cláudio Botazzo ; Liang, Zhao

    Source: Lecture Notes in Artificial Intelligence. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidades: ICMC, FFCLRP

    Subjects: ANÁLISE DE REGRESSÃO E DE CORRELAÇÃO, COVID-19, REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL

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      COLLIRI, Tiago Santos e DELBEM, Alexandre Cláudio Botazzo e LIANG, Zhao. Predicting the evolution of COVID-19 cases and deaths through a correlations-based temporal network. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-61380-8_27. Acesso em: 30 ago. 2024. , 2020

    • APA

      Colliri, T. S., Delbem, A. C. B., & Liang, Z. (2020). Predicting the evolution of COVID-19 cases and deaths through a correlations-based temporal network. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-030-61380-8_27

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      Colliri TS, Delbem ACB, Liang Z. Predicting the evolution of COVID-19 cases and deaths through a correlations-based temporal network [Internet]. Lecture Notes in Artificial Intelligence. 2020 ; 12320 397-411.[citado 2024 ago. 30 ] Available from: https://doi.org/10.1007/978-3-030-61380-8_27

    • Vancouver

      Colliri TS, Delbem ACB, Liang Z. Predicting the evolution of COVID-19 cases and deaths through a correlations-based temporal network [Internet]. Lecture Notes in Artificial Intelligence. 2020 ; 12320 397-411.[citado 2024 ago. 30 ] Available from: https://doi.org/10.1007/978-3-030-61380-8_27

  • Artigo de periodico

    Analyzing the Bills-Voting dynamics and predicting corruption-convictions among brazilian congressmen through temporal networks (2019)

    Colliri, Tiago Santos ; Liang, Zhao

    Source: Scientific Reports. Unidades: FFCLRP, ICMC

    Subjects: REDES COMPLEXAS, ANÁLISE DE SÉRIES TEMPORAIS, CONGRESSO NACIONAL, CORRUPÇÃO

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      COLLIRI, Tiago Santos e LIANG, Zhao. Analyzing the Bills-Voting dynamics and predicting corruption-convictions among brazilian congressmen through temporal networks. Scientific Reports, v. No 2019, p. 16754-1-16754-11, 2019Tradução . . Disponível em: https://doi.org/10.1038/s41598-019-53252-9. Acesso em: 30 ago. 2024.

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      Colliri, T. S., & Liang, Z. (2019). Analyzing the Bills-Voting dynamics and predicting corruption-convictions among brazilian congressmen through temporal networks. Scientific Reports, No 2019, 16754-1-16754-11. doi:10.1038/s41598-019-53252-9

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      Colliri TS, Liang Z. Analyzing the Bills-Voting dynamics and predicting corruption-convictions among brazilian congressmen through temporal networks [Internet]. Scientific Reports. 2019 ; No 2019 16754-1-16754-11.[citado 2024 ago. 30 ] Available from: https://doi.org/10.1038/s41598-019-53252-9

    • Vancouver

      Colliri TS, Liang Z. Analyzing the Bills-Voting dynamics and predicting corruption-convictions among brazilian congressmen through temporal networks [Internet]. Scientific Reports. 2019 ; No 2019 16754-1-16754-11.[citado 2024 ago. 30 ] Available from: https://doi.org/10.1038/s41598-019-53252-9

  • 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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      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: 30 ago. 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 ago. 30 ] 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 ago. 30 ] 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: 30 ago. 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 ago. 30 ] 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 ago. 30 ] Available from: https://doi.org/10.1109/BRACIS.2019.00118

  • Trabalho de evento

    A network-based high level data classification technique (2018)

    Colliri, Tiago Santos; Ji, Donghong; Pan, Heng; Liang, Zhao

    Source: Annals. Conference titles: International Joint Conference on Neural Networks - IJCNN. Unidades: FFCLRP, ICMC

    Subjects: REDES NEURAIS, TECNOLOGIA

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    • ABNT

      COLLIRI, Tiago Santos et al. A network-based high level data classification technique. 2018, Anais.. Rio de Janeiro: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, 2018. Disponível em: https://doi.org/10.1109/ijcnn.2018.8489081. Acesso em: 30 ago. 2024.

    • APA

      Colliri, T. S., Ji, D., Pan, H., & Liang, Z. (2018). A network-based high level data classification technique. In Annals. Rio de Janeiro: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. doi:10.1109/ijcnn.2018.8489081

    • NLM

      Colliri TS, Ji D, Pan H, Liang Z. A network-based high level data classification technique [Internet]. Annals. 2018 ;[citado 2024 ago. 30 ] Available from: https://doi.org/10.1109/ijcnn.2018.8489081

    • Vancouver

      Colliri TS, Ji D, Pan H, Liang Z. A network-based high level data classification technique [Internet]. Annals. 2018 ;[citado 2024 ago. 30 ] Available from: https://doi.org/10.1109/ijcnn.2018.8489081

  • 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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      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: 30 ago. 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 ago. 30 ] 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 ago. 30 ] Available from: https://doi.org/10.1109/CEC.2018.8477891

  • Tese (Doutorado)

    Collective dynamics in complex networks for machine learning (2018)

    Verri, Filipe Alves Neto; Liang, Zhao (Orientador)

    Unidade: ICMC

    Subjects: APRENDIZADO COMPUTACIONAL, REDES COMPLEXAS, HEURÍSTICA

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    • ABNT

      VERRI, Filipe Alves Neto. Collective dynamics in complex networks for machine learning. 2018. Tese (Doutorado) – Universidade de São Paulo, São Carlos, 2018. Disponível em: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-18102018-113054/. Acesso em: 30 ago. 2024.

    • APA

      Verri, F. A. N. (2018). Collective dynamics in complex networks for machine learning (Tese (Doutorado). Universidade de São Paulo, São Carlos. Recuperado de http://www.teses.usp.br/teses/disponiveis/55/55134/tde-18102018-113054/

    • NLM

      Verri FAN. Collective dynamics in complex networks for machine learning [Internet]. 2018 ;[citado 2024 ago. 30 ] Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-18102018-113054/

    • Vancouver

      Verri FAN. Collective dynamics in complex networks for machine learning [Internet]. 2018 ;[citado 2024 ago. 30 ] Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-18102018-113054/

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