activity
20192023
most citedDecoding machine learning benchmarks

15 citations · 28 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2023

-IRT: A New -IRT with Enhanced Discrimination Estimation

Manuel Ferreira-Junior, Jessica T. S. Reinaldo, Telmo M. Silva Filho +2

Item response theory aims to estimate respondent's latent skills from their responses in tests composed of items with different levels of difficulty. Several models of item respons…

cs.LG2022★ 2 cited

Explanation-by-Example Based on Item Response Theory

Lucas F. F. Cardoso, José de S. Ribeiro, Vitor C. A. Santos +4

Intelligent systems that use Machine Learning classification algorithms are increasingly common in everyday society. However, many systems use black-box models that do not have cha…

cs.LG2021★ 5 cited

Label noise detection under the Noise at Random model with ensemble filters

Kecia G. Moura, Ricardo B. C. Prudêncio, George D. C. Cavalcanti

Label noise detection has been widely studied in Machine Learning because of its importance in improving training data quality. Satisfactory noise detection has been achieved by ad…

cs.NE2021

Meta-aprendizado para otimizacao de parametros de redes neurais

Tarsicio Lucas, Teresa Ludermir, Ricardo Prudencio +1

The optimization of Artificial Neural Networks (ANNs) is an important task to the success of using these models in real-world applications. The solutions adopted to this task are e…

cs.LG2021★ 1 cited

Data vs classifiers, who wins?

Lucas F. F. Cardoso, Vitor C. A. Santos, Regiane S. Kawasaki Francês +2

The experiments covered by Machine Learning (ML) must consider two important aspects to assess the performance of a model: datasets and algorithms. Robust benchmarks are needed to…

cs.LG2020★ 15 cited

Decoding machine learning benchmarks

Lucas F. F. Cardoso, Vitor C. A. Santos, Regiane S. K. Francês +2

Despite the availability of benchmark machine learning (ML) repositories (e.g., UCI, OpenML), there is no standard evaluation strategy yet capable of pointing out which is the best…

stat.ML2019★ 5 cited

-IRT: A New Item Response Model and its Applications

Yu Chen, Telmo Silva Filho, Ricardo B. C. Prudêncio +2

Item Response Theory (IRT) aims to assess latent abilities of respondents based on the correctness of their answers in aptitude test items with different difficulty levels. In this…