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2020 – today
- 2024
[c4]Maria Gabriela Valeriano
, João Luiz Junho Pereira, Carlos Roberto Veiga Kiffer, Ana Carolina Lorena:
Explaining instances in the health domain based on the exploration of a dataset's hardness embedding. GECCO Companion 2024: 1598-1606- [c3]Ricardo B. C. Prudêncio, Ana Carolina Lorena, Telmo de Menezes e Silva Filho, Patrícia Drapal, Maria Gabriela Valeriano:
Assessor Models for Explaining Instance Hardness in Classification Problems. IJCNN 2024: 1-8 - 2023
- [c2]Maria Gabriela Valeriano, Pedro Yuri Arbs Paiva, Carlos Roberto Veiga Kiffer, Ana Carolina Lorena:
A Framework for Characterizing What Makes an Instance Hard to Classify. BRACIS (2) 2023: 353-367 - 2022
- [j2]Pedro Yuri Arbs Paiva, Camila Castro Moreno, Kate Smith-Miles, Maria Gabriela Valeriano, Ana Carolina Lorena:
Relating instance hardness to classification performance in a dataset: a visual approach. Mach. Learn. 111(8): 3085-3123 (2022) - [c1]Maria Gabriela Valeriano, Carlos Roberto Veiga Kiffer, Giane Higino, Paloma Zanão, Dulce A. Barbosa, Patrícia A. Moreira, Paulo Caleb J. L. Santos, Renato Grinbaum, Ana Carolina Lorena:
Let the data speak: analysing data from multiple health centers of the São Paulo metropolitan area for COVID-19 clinical deterioration prediction. CCGRID 2022: 948-951 - 2021
- [j1]Leila Abuabara, Maria Gabriela Valeriano, Carlos Roberto Veiga Kiffer, Horacio Hideki Yanasse, Ana Carolina Lorena:
Using Machine Learning to support health system planning during the Covid-19 pandemic: a case study using data from São José dos Campos (Brazil). CLEI Electron. J. 24(3) (2021) - [i1]Pedro Yuri Arbs Paiva, Kate Smith-Miles, Maria Gabriela Valeriano, Ana Carolina Lorena:
PyHard: a novel tool for generating hardness embeddings to support data-centric analysis. CoRR abs/2109.14430 (2021)
Coauthor Index
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