no code implementations • 6 Apr 2024 • Iury B. de A. Santos, André C. P. L. F. de Carvalho
This approach aims to address both challenges by focusing on the medical imaging context and utilizing an inherently interpretable model based on prototypes.
no code implementations • 20 Feb 2024 • Angelo G. Menezes, Augusto J. Peterlevitz, Mateus A. Chinelatto, André C. P. L. F. de Carvalho
Continual Object Detection is essential for enabling intelligent agents to interact proactively with humans in real-world settings.
no code implementations • 30 May 2022 • Angelo G. Menezes, Gustavo de Moura, Cézanne Alves, André C. P. L. F. de Carvalho
The field of Continual Learning investigates the ability to learn consecutive tasks without losing performance on those previously learned.
no code implementations • PROPOR 2022 2022 • Hidelberg O. Albuquerque, Rosimeire Costa, Gabriel Silvestre, Ellen Souza, Nádia F. F. da Silva, Douglas Vitório, Gyovana Moriyama, Lucas Martins, Luiza Soezima, Augusto Nunes, Felipe Siqueira, João P. Tarrega, Joao V. Beinotti, Marcio Dias, Matheus Silva, Miguel Gardini, Vinicius Silva, André C. P. L. F. de Carvalho, Adriano L. I. Oliveira
The amount of legislative documents produced within the past decade has risen dramatically, making it difficult for law practitioners to consult and update legislation.
no code implementations • 22 Oct 2021 • Douglas Castilho, Tharsis T. P. Souza, Soong Moon Kang, João Gama, André C. P. L. F. de Carvalho
For such, market structure is modeled as a dynamic asset network by quantifying time-dependent co-movement of asset price returns across company constituents of major global market indices.
no code implementations • 16 Sep 2020 • Márcio P. Basgalupp, Rodrigo C. Barros, Alex G. C. de Sá, Gisele L. Pappa, Rafael G. Mantovani, André C. P. L. F. de Carvalho, Alex A. Freitas
Auto-WEKA combines algorithm selection and hyper-parameter optimisation to recommend classification algorithms from multiple paradigms.
no code implementations • 25 Oct 2018 • Kemilly Dearo Garcia, Tiago Carvalho, João Mendes-Moreira, João M. P. Cardoso, André C. P. L. F. de Carvalho
In this paper, we present a semi-supervised classifier and a study regarding the influence of hyperparameter configuration in classification accuracy, depending on the user and the activities performed by each user.
2 code implementations • 30 Aug 2018 • Adriano Rivolli, Luís P. F. Garcia, Carlos Soares, Joaquin Vanschoren, André C. P. L. F. de Carvalho
These characterizations, also called meta-features, describe properties of the data which are predictive for the performance of machine learning algorithms trained on them.
3 code implementations • 23 Jul 2018 • Tiago Cunha, Carlos Soares, André C. P. L. F. de Carvalho
However, the results have shown that the feature selection procedure used to create the comprehensive metafeatures is is not effective, since there is no gain in predictive performance.