Pedro Yuri Arbs Paiva

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Produções bibliográficas

• PAIVA, PEDRO YURI ARBS ; MORENO, CAMILA CASTRO ; SMITH-MILES, KATE ; VALERIANO, MARIA GABRIELA ; LORENA, ANA CAROLINA . Relating instance hardness to classification performance in a dataset: a visual approach. MACHINE LEARNING , v. 111, p. 3085-3123, 2022.

• ARBACHE, SAMIR ; MATTOS, ELIZABETH DA COSTA ; DINIZ, MILTON F. ; PAIVA, PEDRO Y. A. ; ROTH, DIRLENE ; ARBACHE, SAMIA T. ; OLIVEIRA, EDNA L. T. ; MICHALANY, NILCEO S. ; HIRATA, SERGIO H. . How much medication is delivered in a novel drug delivery technique that uses a tattoo machine?. INTERNATIONAL JOURNAL OF DERMATOLOGY , v. 58, p. 750-755, 2019.

• TORQUETE, G. P. ; NUNES, V. S. ; PAIVA, P. Y. A. ; CUNHA NETO, L. B. ; LORENA, A. C. . Characterizing instance hardness in classification and regression problems. In: Symposium on Knowledge Discovery, Mining and Learning (KDMiLe), 2022, Campinas. Knowledge Discovery, Mining and Learning Proceedings, 2022.

• PAIVA, P. Y. A. ; SMITH-MILES, K. ; VALERIANO, M. G. ; LORENA, A. C. . PyHard: a novel tool for generating hardness embeddings to support data-centric analysis. In: 1st NeurIPS Workshop on Data Centric AI (DCAI 2021), 2021, Sydney. Proceedings 1st NeurIPS Workshop on Data Centric AI (DCAI 2021), 2021.

• MORENO, C. C. ; PAIVA, P. Y. A. ; NUNES, G. H. ; LORENA, A. C. . Contrasting the Profiles of Easy and Hard Observations in a Dataset. In: 1st NeurIPS Workshop on Data Centric AI (DCAI 2021), 2021, Sydney. Proceedings 1st NeurIPS Workshop on Data Centric AI (DCAI 2021), 2021.

• ARBS PAIVA, PEDRO YURI ; SAOTOME, OSAMU ; BRANDAUER, CHRISTOF . Specification and Verification of a Multi-agent Coordination Protocol with TLA+. In: 2018 VIII Brazilian Symposium on Computing Systems Engineering (SBESC), 2018, Salvador. 2018 VIII Brazilian Symposium on Computing Systems Engineering (SBESC), 2018. p. 207.

• BRANDAUER, CHRISTOF ; DORFINGER, PETER ; PAIVA, PEDRO YURI ARBS . Towards scalable and adaptable security monitoring. In: 2017 IEEE 36th International Performance Computing and Communications Conference (IPCCC), 2017, San Diego. 2017 IEEE 36th International Performance Computing and Communications Conference (IPCCC), 2017. p. 1.

• PAIVA, P. Y. A. ; BRANDAUER, C. ; SAOTOME, O. . Demonstrating the feasibility of a new security monitoring framework for SCADA systems. In: Brazilian Technology Symposium, 2017, Campinas. BTSym?17 proceedings, 2017. v. 1.

• PAIVA, P. Y. A. ; EGUTI, C. C. A. . Comparação entre K-Means e rede neural de Kohonen para segmentação de imagens por cor. In: XIX Encontro de Iniciação Científica e Pós-Graduação do ITA, 2013, São José dos Campos. Anais do XIX ENCITA.

• LORENA, ANA C. ; PAIVA, PEDRO Y. A. ; PRUDÊNCIO, RICARDO B. C. . Trusting my predictions: on the value of Instance-Level analysis. ACM COMPUTING SURVEYS , 2023.

• TORQUETE, G. P. ; NUNES, V. S. ; PAIVA, P. Y. A. ; CUNHA NETO, L. B. ; LORENA, A. C. . Characterizing instance hardness in classification and regression problems. 2022. (Apresentação de Trabalho/Simpósio).

• ARBS PAIVA, PEDRO YURI . PyHard: a novel tool for generating hardness embeddings to support data-centric analysis. 2021. (Apresentação de Trabalho/Conferência ou palestra).

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