15 citations · 20 across the 7 of their papers we have counts for
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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.LG2021
Does Dataset Complexity Matters for Model Explainers?
José Ribeiro, Raíssa Silva, Lucas Cardoso +1
Strategies based on Explainable Artificial Intelligence - XAI have emerged in computing to promote a better understanding of predictions made by black box models. Most XAI measures…