| Aprendizagem colaborativa com suporte computacional: Uma perspectiva histórica G Stahl, T Koschmann, D Suthers, H Fuks, T Escovedo Boletim Gepem, 2008 | 72 | 2008 |
| DetectA: abrupt concept drift detection in non-stationary environments T Escovedo, A Koshiyama, AA da Cruz, M Vellasco Applied Soft Computing 62, 119-133, 2018 | 66 | 2018 |
| Requirements engineering for machine learning: A systematic mapping study H Villamizar, T Escovedo, M Kalinowski 2021 47th Euromicro Conference on Software Engineering and Advanced …, 2021 | 65 | 2021 |
| Introdução a Data Science: Algoritmos de Machine Learning e métodos de análise T Escovedo, A Koshiyama | 36 | 2020 |
| Using business processes in system requirements definition EA Carvalho, T Escovedo, RN Melo 2009 33rd Annual IEEE Software Engineering Workshop, 125-130, 2009 | 22 | 2009 |
| Engenharia de Software para Ciência de Dados: Um guia de boas práticas com ênfase na construção de sistemas de Machine Learning em Python M Kalinowski, T Escovedo, H Villamizar, H Lopes Casa do Código, 2023 | 14 | 2023 |
| GPF-class: a genetic fuzzy model for classification AS Koshiyama, T Escovedo, DM Dias, MMBR Vellasco, R Tanscheit 2013 IEEE Congress on Evolutionary Computation, 3275-3282, 2013 | 14 | 2013 |
| Avaliei, avaliei... ensinei? Investigações sobre avaliação nas conferências de um curso online T Escovedo, M Pimentel, H Fuks, CJP de Lucena Anais do Workshop de Informática na Escola 1 (1), 2006 | 12 | 2006 |
| Status quo and problems of requirements engineering for machine learning: Results from an international survey APS Alves, M Kalinowski, G Giray, D Mendez, N Lavesson, K Azevedo, ... International Conference on Product-Focused Software Process Improvement …, 2023 | 10 | 2023 |
| Investigating the Impact of SOLID Design Principles on Machine Learning Code Understanding R Cabral, M Kalinowski, MT Baldassarre, H Villamizar, T Escovedo, ... Proceedings of the IEEE/ACM 3rd International Conference on AI Engineering …, 2024 | 9 | 2024 |
| Neuroevolutionary learning in nonstationary environments T Escovedo, A Koshiyama, AA da Cruz, M Vellasco Applied Intelligence 50 (5), 1590-1608, 2020 | 9 | 2020 |
| Neve++: A neuro-evolutionary unlimited ensemble for adaptive learning T Escovedo, AA da Cruz, A Koshiyama, R Melo, M Vellasco 2014 International Joint Conference on Neural Networks (IJCNN), 3331-3338, 2014 | 9 | 2014 |
| Learning under concept drift using a neuro-evolutionary ensemble T Escovedo, AVABS DA CRUZ, MMBR VELLASCO, AS Koshiyama International Journal of Computational Intelligence and Applications 12 (04 …, 2013 | 9 | 2013 |
| Uma análise comparativa entre as ferramentas OLAP como apoio a soluções de BI nas empresas T Sá, A METEUS, M Iwanaga, A Ribeiro, T Escovedo, RN Melo Rio de Janeiro: PUC RIO, 2012 | 9 | 2012 |
| GPFIS-Control: A fuzzy Genetic model for Control tasks AS Koshiyama, T Escovedo, MMBR Vellasco, R Tanscheit 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1953-1959, 2014 | 7 | 2014 |
| ML-Enabled Systems Model Deployment and Monitoring: Status Quo and Problems E Zimelewicz, M Kalinowski, D Mendez, G Giray, AP Santos Alves, ... International Conference on Software Quality, 112-131, 2024 | 6 | 2024 |
| Neve: A neuro-evolutionary ensemble for adaptive learning T Escovedo, AVA da Cruz, M Vellasco, AS Koshiyama Artificial Intelligence Applications and Innovations: 9th IFIP WG 12.5 …, 2013 | 5 | 2013 |
| Using ensembles for adaptive learning: A comparative approach T Escovedo, AVA da Cruz, M Vellasco, AS Koshiyama The 2013 International Joint Conference on Neural Networks (IJCNN), 1-7, 2013 | 4 | 2013 |
| Combining Forecasts: A Genetic Programming Approach AS Koshiyama, T Escovedo, DM Dias, MMBR Vellasco, MAC Pacheco International Journal of Natural Computing Research (IJNCR) 3 (3), 41-58, 2012 | 4 | 2012 |
| Avaliei, Avaliei T Escovedo, M Pimentel, H Fuks, CJP Lucena Ensinei, 2006 | 4 | 2006 |
Marcos KalinowskiProfessor, Pontifical Catholic University of Rio de Janeiro (PUC-Rio)Потвърден имейл адрес: inf.puc-rio.br
