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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: 09 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. 09 ] 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. 09 ] Available from: https://doi.org/10.1109/IJCNN60899.2024.10650514
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: 09 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. 09 ] 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. 09 ] Available from: https://doi.org/10.1109/IJCNN54540.2023.10191134
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: 09 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. 09 ] 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. 09 ] Available from: https://doi.org/10.1145/3617023.3617038
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: 09 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. 09 ] 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. 09 ] Available from: https://doi.org/10.1109/IJCNN54540.2023.10191004
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: 09 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. 09 ] 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. 09 ] Available from: https://doi.org/10.1109/IJCNN48605.2020.9206755
Trabalho de evento
Measuring the engagement level in encrypted group conversations by using temporal networks (2020)
Cotacallapa, Moshe; Berton, Lilian; Ferreira, Leonardo N.; Quiles, Marcos Gonçalves; Liang, Zhao; Macau, Elbert E. N.; Vega-Oliveros, Didier Augusto
Source: Proceedings. Conference titles: International Joint Conference on Neural Networks - IJCNN. Unidade: FFCLRP
Subjects: MENSAGEM, CHAT, CRIPTOLOGIA, PRIVACIDADE, FRAMEWORKS
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ABNT
COTACALLAPA, Moshe et al. Measuring the engagement level in encrypted group conversations by using temporal networks. 2020, Anais.. Los Alamitos: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, 2020. Disponível em: https://doi.org/10.1109/IJCNN48605.2020.9207174. Acesso em: 09 nov. 2024.
APA
Cotacallapa, M., Berton, L., Ferreira, L. N., Quiles, M. G., Liang, Z., Macau, E. E. N., & Vega-Oliveros, D. A. (2020). Measuring the engagement level in encrypted group conversations by using temporal networks. In Proceedings. Los Alamitos: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. doi:10.1109/IJCNN48605.2020.9207174
NLM
Cotacallapa M, Berton L, Ferreira LN, Quiles MG, Liang Z, Macau EEN, Vega-Oliveros DA. Measuring the engagement level in encrypted group conversations by using temporal networks [Internet]. Proceedings. 2020 ;[citado 2024 nov. 09 ] Available from: https://doi.org/10.1109/IJCNN48605.2020.9207174
Vancouver
Cotacallapa M, Berton L, Ferreira LN, Quiles MG, Liang Z, Macau EEN, Vega-Oliveros DA. Measuring the engagement level in encrypted group conversations by using temporal networks [Internet]. Proceedings. 2020 ;[citado 2024 nov. 09 ] Available from: https://doi.org/10.1109/IJCNN48605.2020.9207174
Trabalho de evento
A new network-base high-level data classification methodology (Quipus) by modeling attribute-attribute interactions (2020)
Zuñiga, Esteban Wilfredo Vilca ; Liang, Zhao
Source: Proceedings. Conference titles: International Conference of Digital Transformation and Innovation Technology - Incodtrin. Unidade: FFCLRP
Subjects: MATEMÁTICA APLICADA, APRENDIZADO COMPUTACIONAL, ALGORITMOS
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ABNT
ZUÑIGA, Esteban Wilfredo Vilca e LIANG, Zhao. A new network-base high-level data classification methodology (Quipus) by modeling attribute-attribute interactions. 2020, Anais.. Manchester: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, 2020. Disponível em: https://www.researchgate.net/publication/344411081_A_new_network-base_high-level_data_classification_methodology_Quipus_by_modeling_attribute-attribute_interactions. Acesso em: 09 nov. 2024.
APA
Zuñiga, E. W. V., & Liang, Z. (2020). A new network-base high-level data classification methodology (Quipus) by modeling attribute-attribute interactions. In Proceedings. Manchester: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. Recuperado de https://www.researchgate.net/publication/344411081_A_new_network-base_high-level_data_classification_methodology_Quipus_by_modeling_attribute-attribute_interactions
NLM
Zuñiga EWV, Liang Z. A new network-base high-level data classification methodology (Quipus) by modeling attribute-attribute interactions [Internet]. Proceedings. 2020 ;[citado 2024 nov. 09 ] Available from: https://www.researchgate.net/publication/344411081_A_new_network-base_high-level_data_classification_methodology_Quipus_by_modeling_attribute-attribute_interactions
Vancouver
Zuñiga EWV, Liang Z. A new network-base high-level data classification methodology (Quipus) by modeling attribute-attribute interactions [Internet]. Proceedings. 2020 ;[citado 2024 nov. 09 ] Available from: https://www.researchgate.net/publication/344411081_A_new_network-base_high-level_data_classification_methodology_Quipus_by_modeling_attribute-attribute_interactions
Trabalho de evento
Clustered echo state networks for signal observation and frequency filtering (2020)
Oliveira Junior, Laercio de; Stelzer, Florian; Liang, Zhao
Source: Proceedings. Conference titles: Symposium on Knowledge Discovery, Mining and Learning - KDMiLe. Unidade: FFCLRP
Subjects: REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL, REDES NEURAIS
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ABNT
OLIVEIRA JUNIOR, Laercio de e STELZER, Florian e LIANG, Zhao. Clustered echo state networks for signal observation and frequency filtering. 2020, Anais.. Porto Alegre: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, 2020. Disponível em: https://doi.org/10.5753/kdmile.2020.11955. Acesso em: 09 nov. 2024.
APA
Oliveira Junior, L. de, Stelzer, F., & Liang, Z. (2020). Clustered echo state networks for signal observation and frequency filtering. In Proceedings. Porto Alegre: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. doi:10.5753/kdmile.2020.11955
NLM
Oliveira Junior L de, Stelzer F, Liang Z. Clustered echo state networks for signal observation and frequency filtering [Internet]. Proceedings. 2020 ;[citado 2024 nov. 09 ] Available from: https://doi.org/10.5753/kdmile.2020.11955
Vancouver
Oliveira Junior L de, Stelzer F, Liang Z. Clustered echo state networks for signal observation and frequency filtering [Internet]. Proceedings. 2020 ;[citado 2024 nov. 09 ] Available from: https://doi.org/10.5753/kdmile.2020.11955
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: 09 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. 09 ] 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. 09 ] Available from: https://doi.org/10.1109/ColCACI50549.2020.9248714
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: 09 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. 09 ] 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. 09 ] 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: 09 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. 09 ] 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. 09 ] 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: 09 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. 09 ] 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. 09 ] Available from: https://doi.org/10.1109/CEC.2018.8477891
Trabalho de evento
Structural outlier detection: a tourist walk approach (2017)
Rodrigues, Rafael D.; Liang, Zhao; Zheng, Qiusheng; Zhang, Junbao
Source: Proceedings. Conference titles: International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery. Unidade: FFCLRP
Assunto: MINERAÇÃO DE DADOS
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ABNT
RODRIGUES, Rafael D. et al. Structural outlier detection: a tourist walk approach. 2017, Anais.. Guilin: IEEE, 2017. . Acesso em: 09 nov. 2024.
APA
Rodrigues, R. D., Liang, Z., Zheng, Q., & Zhang, J. (2017). Structural outlier detection: a tourist walk approach. In Proceedings. Guilin: IEEE.
NLM
Rodrigues RD, Liang Z, Zheng Q, Zhang J. Structural outlier detection: a tourist walk approach. Proceedings. 2017 ;[citado 2024 nov. 09 ]
Vancouver
Rodrigues RD, Liang Z, Zheng Q, Zhang J. Structural outlier detection: a tourist walk approach. Proceedings. 2017 ;[citado 2024 nov. 09 ]
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: 09 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. 09 ] 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. 09 ] Available from: https://doi.org/10.1109/FSKD.2017.8393113
Trabalho de evento
Nature-inspired graph optimization for dimensionality reduction (2017)
Carneiro, Murillo G.; Cupertino, Thiago H.; Cheng, Ran; Jin, Yaochu; Liang, Zhao
Source: Proceedings. Conference titles: International Conference on Tools with Artficial Intelligence. Unidade: FFCLRP
Subjects: APRENDIZADO COMPUTACIONAL, INTELIGÊNCIA ARTIFICIAL
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ABNT
CARNEIRO, Murillo G. et al. Nature-inspired graph optimization for dimensionality reduction. 2017, Anais.. Boston: IEEE, 2017. . Acesso em: 09 nov. 2024.
APA
Carneiro, M. G., Cupertino, T. H., Cheng, R., Jin, Y., & Liang, Z. (2017). Nature-inspired graph optimization for dimensionality reduction. In Proceedings. Boston: IEEE.
NLM
Carneiro MG, Cupertino TH, Cheng R, Jin Y, Liang Z. Nature-inspired graph optimization for dimensionality reduction. Proceedings. 2017 ;[citado 2024 nov. 09 ]
Vancouver
Carneiro MG, Cupertino TH, Cheng R, Jin Y, Liang Z. Nature-inspired graph optimization for dimensionality reduction. Proceedings. 2017 ;[citado 2024 nov. 09 ]
Trabalho de evento
Low and high level classification using stacking (2017)
Covões, Thiago Ferreira; Liang, Zhao
Source: Proceedings. Conference titles: International Joint Conference on Neural Networks - IJCNN. Unidade: FFCLRP
Assunto: REDES NEURAIS
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ABNT
COVÕES, Thiago Ferreira e LIANG, Zhao. Low and high level classification using stacking. 2017, Anais.. Anchorage: INNS, 2017. Disponível em: https://doi.org/10.1109/IJCNN.2017.7966163. Acesso em: 09 nov. 2024.
APA
Covões, T. F., & Liang, Z. (2017). Low and high level classification using stacking. In Proceedings. Anchorage: INNS. doi:10.1109/IJCNN.2017.7966163
NLM
Covões TF, Liang Z. Low and high level classification using stacking [Internet]. Proceedings. 2017 ;[citado 2024 nov. 09 ] Available from: https://doi.org/10.1109/IJCNN.2017.7966163
Vancouver
Covões TF, Liang Z. Low and high level classification using stacking [Internet]. Proceedings. 2017 ;[citado 2024 nov. 09 ] Available from: https://doi.org/10.1109/IJCNN.2017.7966163
Trabalho de evento
Data classification in complex networks via pattern conformation, data importance and structural optimization (2017)
Carneiro, Murillo Guimarães; Liang, Zhao
Source: Proceedings. Conference titles: Brazilian Symposium on Databases (SBBD). Unidade: FFCLRP
Assunto: REDES COMPLEXAS
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ABNT
CARNEIRO, Murillo Guimarães e LIANG, Zhao. Data classification in complex networks via pattern conformation, data importance and structural optimization. 2017, Anais.. Uberlândia: Sociedade Brasileira de Computação, 2017. . Acesso em: 09 nov. 2024.
APA
Carneiro, M. G., & Liang, Z. (2017). Data classification in complex networks via pattern conformation, data importance and structural optimization. In Proceedings. Uberlândia: Sociedade Brasileira de Computação.
NLM
Carneiro MG, Liang Z. Data classification in complex networks via pattern conformation, data importance and structural optimization. Proceedings. 2017 ;[citado 2024 nov. 09 ]
Vancouver
Carneiro MG, Liang Z. Data classification in complex networks via pattern conformation, data importance and structural optimization. Proceedings. 2017 ;[citado 2024 nov. 09 ]
Trabalho de evento
A new evaluation function for clustering: the NK internal validation criterion (2016)
Tinós, Renato; Chicano, Francisco; Liang, Zhao; Whitley, Darrell
Source: Proceedings. Conference titles: Genetic and Evolutionary Computation Conference. Unidade: FFCLRP
Subjects: COMPUTAÇÃO EVOLUTIVA, OTIMIZAÇÃO COMBINATÓRIA
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ABNT
TINÓS, Renato et al. A new evaluation function for clustering: the NK internal validation criterion. 2016, Anais.. Denver: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, 2016. Disponível em: https://doi.org/10.1145/2908812.2908831. Acesso em: 09 nov. 2024.
APA
Tinós, R., Chicano, F., Liang, Z., & Whitley, D. (2016). A new evaluation function for clustering: the NK internal validation criterion. In Proceedings. Denver: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. doi:10.1145/2908812.2908831
NLM
Tinós R, Chicano F, Liang Z, Whitley D. A new evaluation function for clustering: the NK internal validation criterion [Internet]. Proceedings. 2016 ;[citado 2024 nov. 09 ] Available from: https://doi.org/10.1145/2908812.2908831
Vancouver
Tinós R, Chicano F, Liang Z, Whitley D. A new evaluation function for clustering: the NK internal validation criterion [Internet]. Proceedings. 2016 ;[citado 2024 nov. 09 ] Available from: https://doi.org/10.1145/2908812.2908831
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: 09 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. 09 ]
Vancouver
Carneiro MG, Liang Z, Rosa JLG. Graph-based semi-supervised learning for semantic role diffusion. Proceedings. 2016 ;[citado 2024 nov. 09 ]
Trabalho de evento
Semi-supervised learning by edge domination in complex networks (2015)
Urio, Paulo Roberto; Verri, Filipe Alves Neto; Liang, Zhao
Source: Proceedings. Conference titles: International Conference on Natural Computation (ICNC). Unidade: FFCLRP
Subjects: REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
URIO, Paulo Roberto e VERRI, Filipe Alves Neto e LIANG, Zhao. Semi-supervised learning by edge domination in complex networks. 2015, Anais.. Zhangjiajie: IEEE, 2015. . Acesso em: 09 nov. 2024.
APA
Urio, P. R., Verri, F. A. N., & Liang, Z. (2015). Semi-supervised learning by edge domination in complex networks. In Proceedings. Zhangjiajie: IEEE.
NLM
Urio PR, Verri FAN, Liang Z. Semi-supervised learning by edge domination in complex networks. Proceedings. 2015 ;[citado 2024 nov. 09 ]
Vancouver
Urio PR, Verri FAN, Liang Z. Semi-supervised learning by edge domination in complex networks. Proceedings. 2015 ;[citado 2024 nov. 09 ]

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