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Trabalho de evento-anais periodico
Exploring the relationship between feature attribution methods and model performance (2024)
Silva, Priscylla; Silva, Claudio; Nonato, Luis Gustavo
Source: Proceedings of Machine Learning Research. Conference titles: Annual AAAI Conference on Artificial Intelligence. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, APRENDIZAGEM PROFUNDA, ANÁLISE DE DESEMPENHO, EDUCAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SILVA, Priscylla e SILVA, Claudio e NONATO, Luis Gustavo. Exploring the relationship between feature attribution methods and model performance. Proceedings of Machine Learning Research. Vancouver: AAAI. Disponível em: https://proceedings.mlr.press/v257/silva24a.html. Acesso em: 14 nov. 2024. , 2024
APA
Silva, P., Silva, C., & Nonato, L. G. (2024). Exploring the relationship between feature attribution methods and model performance. Proceedings of Machine Learning Research. Vancouver: AAAI. Recuperado de https://proceedings.mlr.press/v257/silva24a.html
NLM
Silva P, Silva C, Nonato LG. Exploring the relationship between feature attribution methods and model performance [Internet]. Proceedings of Machine Learning Research. 2024 ; 257 29-38.[citado 2024 nov. 14 ] Available from: https://proceedings.mlr.press/v257/silva24a.html
Vancouver
Silva P, Silva C, Nonato LG. Exploring the relationship between feature attribution methods and model performance [Internet]. Proceedings of Machine Learning Research. 2024 ; 257 29-38.[citado 2024 nov. 14 ] Available from: https://proceedings.mlr.press/v257/silva24a.html
Artigo de periodico
MOUNTAINEER: topology-driven visual analytics for comparing local explanations (2024)
Solunke, Parikshit ; Guardieiro, Vitoria ; Rulff, João ; Chan, Gromit Yeuk-Yin ; Barr, Brian ; Nonato, Luis Gustavo ; Silva, Claudio
Source: IEEE Transactions on Visualization and Computer Graphics. Unidade: ICMC
Subjects: MODELAGEM DE DADOS, APRENDIZADO COMPUTACIONAL, ESTATÍSTICA, SIMULAÇÃO, TOPOLOGIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SOLUNKE, Parikshit et al. MOUNTAINEER: topology-driven visual analytics for comparing local explanations. IEEE Transactions on Visualization and Computer Graphics, 2024Tradução . . Disponível em: https://doi.org/10.1109/TVCG.2024.3418653. Acesso em: 14 nov. 2024.
APA
Solunke, P., Guardieiro, V., Rulff, J., Chan, G. Y. -Y., Barr, B., Nonato, L. G., & Silva, C. (2024). MOUNTAINEER: topology-driven visual analytics for comparing local explanations. IEEE Transactions on Visualization and Computer Graphics. doi:10.1109/TVCG.2024.3418653
NLM
Solunke P, Guardieiro V, Rulff J, Chan GY-Y, Barr B, Nonato LG, Silva C. MOUNTAINEER: topology-driven visual analytics for comparing local explanations [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2024 ;[citado 2024 nov. 14 ] Available from: https://doi.org/10.1109/TVCG.2024.3418653
Vancouver
Solunke P, Guardieiro V, Rulff J, Chan GY-Y, Barr B, Nonato LG, Silva C. MOUNTAINEER: topology-driven visual analytics for comparing local explanations [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2024 ;[citado 2024 nov. 14 ] Available from: https://doi.org/10.1109/TVCG.2024.3418653
Artigo de periodico
Calibrate: interactive analysis of probabilistic model output (2023)
Xenopoulos, Peter ; Rulff, João; Nonato, Luis Gustavo ; Barr, Brian; Silva, Claudio
Source: IEEE Transactions on Visualization and Computer Graphics. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, VISUALIZAÇÃO, MODELOS PARA PROCESSOS ESTOCÁSTICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
XENOPOULOS, Peter et al. Calibrate: interactive analysis of probabilistic model output. IEEE Transactions on Visualization and Computer Graphics, v. 29, n. Ja 2023, p. 853-863, 2023Tradução . . Disponível em: https://doi.org/10.1109/TVCG.2022.3209489. Acesso em: 14 nov. 2024.
APA
Xenopoulos, P., Rulff, J., Nonato, L. G., Barr, B., & Silva, C. (2023). Calibrate: interactive analysis of probabilistic model output. IEEE Transactions on Visualization and Computer Graphics, 29( Ja 2023), 853-863. doi:10.1109/TVCG.2022.3209489
NLM
Xenopoulos P, Rulff J, Nonato LG, Barr B, Silva C. Calibrate: interactive analysis of probabilistic model output [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2023 ; 29( Ja 2023): 853-863.[citado 2024 nov. 14 ] Available from: https://doi.org/10.1109/TVCG.2022.3209489
Vancouver
Xenopoulos P, Rulff J, Nonato LG, Barr B, Silva C. Calibrate: interactive analysis of probabilistic model output [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2023 ; 29( Ja 2023): 853-863.[citado 2024 nov. 14 ] Available from: https://doi.org/10.1109/TVCG.2022.3209489
Artigo de periodico
SUBPLEX: a Visual analytics approach to understand local model explanations at the subpopulation level (2022)
Yuan, Jun ; Chan, Gromit Yeuk-Yin ; Barr, Brian; Overton, Kyle; Rees, Kim; Nonato, Luis Gustavo ; Bertini, Enrico ; Silva, Claudio Teixeira
Source: IEEE Computer Graphics and Applications. Unidade: ICMC
Subjects: CLUSTERS, VISUALIZAÇÃO, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
YUAN, Jun et al. SUBPLEX: a Visual analytics approach to understand local model explanations at the subpopulation level. IEEE Computer Graphics and Applications, v. 42, n. 6, p. 24-36, 2022Tradução . . Disponível em: https://doi.org/10.1109/MCG.2022.3199727. Acesso em: 14 nov. 2024.
APA
Yuan, J., Chan, G. Y. -Y., Barr, B., Overton, K., Rees, K., Nonato, L. G., et al. (2022). SUBPLEX: a Visual analytics approach to understand local model explanations at the subpopulation level. IEEE Computer Graphics and Applications, 42( 6), 24-36. doi:10.1109/MCG.2022.3199727
NLM
Yuan J, Chan GY-Y, Barr B, Overton K, Rees K, Nonato LG, Bertini E, Silva CT. SUBPLEX: a Visual analytics approach to understand local model explanations at the subpopulation level [Internet]. IEEE Computer Graphics and Applications. 2022 ; 42( 6): 24-36.[citado 2024 nov. 14 ] Available from: https://doi.org/10.1109/MCG.2022.3199727
Vancouver
Yuan J, Chan GY-Y, Barr B, Overton K, Rees K, Nonato LG, Bertini E, Silva CT. SUBPLEX: a Visual analytics approach to understand local model explanations at the subpopulation level [Internet]. IEEE Computer Graphics and Applications. 2022 ; 42( 6): 24-36.[citado 2024 nov. 14 ] Available from: https://doi.org/10.1109/MCG.2022.3199727
Trabalho de evento
Visualization for machine learning (2022)
Xenopoulos, Peter ; Nonato, Luis Gustavo ; Silva, Claudio
Source: Proceedings. Conference titles: Conference on Graphics, Patterns and Images - SIBGRAPI. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, VISUALIZAÇÃO, ANÁLISE DE DADOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
XENOPOULOS, Peter e NONATO, Luis Gustavo e SILVA, Claudio. Visualization for machine learning. 2022, Anais.. Piscataway: IEEE, 2022. Disponível em: https://doi.org/10.1109/SIBGRAPI55357.2022.9991759. Acesso em: 14 nov. 2024.
APA
Xenopoulos, P., Nonato, L. G., & Silva, C. (2022). Visualization for machine learning. In Proceedings. Piscataway: IEEE. doi:10.1109/SIBGRAPI55357.2022.9991759
NLM
Xenopoulos P, Nonato LG, Silva C. Visualization for machine learning [Internet]. Proceedings. 2022 ;[citado 2024 nov. 14 ] Available from: https://doi.org/10.1109/SIBGRAPI55357.2022.9991759
Vancouver
Xenopoulos P, Nonato LG, Silva C. Visualization for machine learning [Internet]. Proceedings. 2022 ;[citado 2024 nov. 14 ] Available from: https://doi.org/10.1109/SIBGRAPI55357.2022.9991759

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