Maria Gabriela Valeriano

According to our database, Maria Gabriela Valeriano authored at least 11 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Filtering Instances and Rejecting Predictions to Obtain Reliable Models in Healthcare.

Maria Gabriela Valeriano, David Kohan Marzagão, Alfredo Montelongo, Carlos Roberto Veiga Kiffer, Natan Katz, Ana Carolina Lorena

Mach. Learn., January, 2026

2025

Beyond Filtering: Leveraging Instance Hardness for Data-Centric Machine Learning in Healthcare.

Maria Gabriela Valeriano, Carlos Roberto Veiga Kiffer, Ana Carolina Lorena

Proceedings of the International Joint Conference on Neural Networks, 2025

Classification with Reject Option: Building Meta-models to Predict Classification Error.

Patricia S. M. Ueda, Maria Gabriela Valeriano, Arthur Dantas Mangussi, Ricardo B. C. Prudêncio, Ana Carolina Lorena

Proceedings of the Intelligent Systems - 35th Brazilian Conference, 2025

2024

Understanding the performance of machine learning models from data- to patient-level.

Maria Gabriela Valeriano, Ana Matran-Fernandez, Carlos Roberto Veiga Kiffer, Ana Carolina Lorena

ACM J. Data Inf. Qual., December, 2024

Assessor Models for Explaining Instance Hardness in Classification Problems.

Ricardo B. C. Prudêncio, Ana Carolina Lorena, Telmo de Menezes e Silva Filho, Patrícia Drapal, Maria Gabriela Valeriano

Proceedings of the International Joint Conference on Neural Networks, 2024

Explaining instances in the health domain based on the exploration of a dataset's hardness embedding.

Maria Gabriela Valeriano, João Luiz Junho Pereira, Carlos Roberto Veiga Kiffer, Ana Carolina Lorena

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

2023

A Framework for Characterizing What Makes an Instance Hard to Classify.

Maria Gabriela Valeriano, Pedro Yuri Arbs Paiva, Carlos Roberto Veiga Kiffer, Ana Carolina Lorena

Proceedings of the Intelligent Systems - 12th Brazilian Conference, 2023

2022

Relating instance hardness to classification performance in a dataset: a visual approach.

Pedro Yuri Arbs Paiva, Camila Castro Moreno, Kate Smith-Miles, Maria Gabriela Valeriano, Ana Carolina Lorena

Mach. Learn., 2022

Let the data speak: analysing data from multiple health centers of the São Paulo metropolitan area for COVID-19 clinical deterioration prediction.

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

Proceedings of the 22nd IEEE International Symposium on Cluster, 2022

2021

PyHard: a novel tool for generating hardness embeddings to support data-centric analysis.

Pedro Yuri Arbs Paiva, Kate Smith-Miles, Maria Gabriela Valeriano, Ana Carolina Lorena

CoRR, 2021

Using Machine Learning to support health system planning during the Covid-19 pandemic: a case study using data from São José dos Campos (Brazil).

Leila Abuabara, Maria Gabriela Valeriano, Carlos Roberto Veiga Kiffer, Horacio Hideki Yanasse, Ana Carolina Lorena

CLEI Electron. J., 2021