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Tatiana Escovedo
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2020 – today
- 2024
- [c26]Raphael Cabral
, Marcos Kalinowski
Investigating the Impact of SOLID Design Principles on Machine Learning Code Understanding. CAIN 2024: 7-17 - [c25]Antonio Pedro Santos Alves, Marcos Kalinowski, Daniel Méndez, Hugo Villamizar, Kelly Azevedo, Tatiana Escovedo, Hélio Lopes:
Industrial Practices of Requirements Engineering for ML-Enabled Systems in Brazil. SBES 2024: 224-233 - [c24]Ezequiel Mule Jorge
Investigating Predicting Voluntary Resignation Program Participation with Machine Learning. SBSI 2024: 54:1-54:10 - [c23]Gustavo Morais
Machine Learning Applied in the Construction of a Disability Retirement Entry Table of the General Social Security Regime (RGPS) of Brazil. SBSI 2024: 55:1-55:10 - [c22]Eduardo Zimelewicz
ML-Enabled Systems Model Deployment and Monitoring: Status Quo and Problems. SWQD 2024: 112-131 - [i6]Eduardo Zimelewicz, Marcos Kalinowski, Daniel Méndez, Görkem Giray, Antonio Pedro Santos Alves, Niklas Lavesson, Kelly Azevedo, Hugo Villamizar, Tatiana Escovedo, Hélio Lopes, Stefan Biffl, Juergen Musil, Michael Felderer, Stefan Wagner, Maria Teresa Baldassarre, Tony Gorschek:
ML-Enabled Systems Model Deployment and Monitoring: Status Quo and Problems. CoRR abs/2402.05333 (2024) - [i5]Raphael Cabral, Marcos Kalinowski, Maria Teresa Baldassarre, Hugo Villamizar, Tatiana Escovedo, Hélio Lopes:
Investigating the Impact of SOLID Design Principles on Machine Learning Code Understanding. CoRR abs/2402.05337 (2024) - [i4]Marcos Kalinowski, Daniel Méndez, Görkem Giray, Antonio Pedro Santos Alves, Kelly Azevedo, Tatiana Escovedo, Hugo Villamizar, Hélio Lopes, Maria Teresa Baldassarre, Stefan Wagner, Stefan Biffl, Jürgen Musil, Michael Felderer, Niklas Lavesson, Tony Gorschek:
Naming the Pain in Machine Learning-Enabled Systems Engineering. CoRR abs/2406.04359 (2024) - [i3]Antonio Pedro Santos Alves, Marcos Kalinowski, Daniel Méndez, Hugo Villamizar, Kelly Azevedo, Tatiana Escovedo, Hélio Lopes:
Industrial Practices of Requirements Engineering for ML-Enabled Systems in Brazil. CoRR abs/2407.18977 (2024) - 2023
- [c21]Antonio Pedro Santos Alves, Marcos Kalinowski, Görkem Giray, Daniel Méndez, Niklas Lavesson, Kelly Azevedo, Hugo Villamizar, Tatiana Escovedo, Hélio Lopes
Status Quo and Problems of Requirements Engineering for Machine Learning: Results from an International Survey. PROFES (1) 2023: 159-174 - [c20]Marcos Kalinowski
Training the Professionals that Industry Needs: The Digital Software Engineering Education Program at PUC-Rio. SBES 2023: 37-46 - [c19]André Amaral
Machine Learning Applied to the Classification of Technical Inspection Recommendations Regarding the Trend to Increase Criticality. SBSI 2023: 17-27 - [c18]Luciana Silva
Inference of Properties of a Natural Gas Processing Plant Through the Application of Machine Learning to Time Series. SBSI 2023: 102-111 - [c17]Marcelo Abbehusen
Optimizing Wireline Formation Testing in Oil Wells: A Data Science approach. SBSI 2023: 112-119 - [c16]Ramon Vaqueiro
Machine Learning Applied to Open Government Data for the Detection of Improprieties in the Application of Public Resources. SBSI 2023: 213-220 - [d2]Eduardo Zimelewicz
ML-Enabled Systems Model Deployment and Monitoring: Status Quo and Problems. Zenodo, 2023 - [i2]Antonio Pedro Santos Alves, Marcos Kalinowski, Görkem Giray, Daniel Méndez, Niklas Lavesson, Kelly Azevedo, Hugo Villamizar, Tatiana Escovedo, Hélio Lopes, Stefan Biffl, Jürgen Musil, Michael Felderer, Stefan Wagner, Maria Teresa Baldassarre, Tony Gorschek:
Status Quo and Problems of Requirements Engineering for Machine Learning: Results from an International Survey. CoRR abs/2310.06726 (2023) - 2022
- [j6]Ney Barchilon, Tatiana Escovedo, Marcos Kalinowski:
Machine Learning Aplicado ao Resultado de Pedido de Concessão de Benefícios do INSS - Análise Ampliada. Braz. J. Inf. Syst. 15(1) (2022) - [j5]José Douglas Nascimento
Construção de Tábuas de Mortalidade com o uso de Redes Neurais LSTM Bidirectional para Predição das Probabilidades de Morte. Braz. J. Inf. Syst. 15(1) (2022) - [c15]Flávia Bravo, Luciana Sousa, Tatiana Escovedo
Machine Learning Aplicado à Predição da Obrigação do Investimento em P, D&I. SBBD 2022: 216-228 - [c14]Marcos Alexandre Castro, Nelson Souza Jr, Tatiana Escovedo
Mineração de Processos Aplicada à Auditoria Interna na Marinha do Brasil. SBBD 2022: 241-253 - [c13]Laércio Lucchesi, Tatiana Escovedo
Padronização da Descrição de Produtos Comerciais utilizando NER. SBBD 2022: 445-450 - [c12]Anna Luiza Gomes, Getúlio Vianna, Tatiana Escovedo, Marcos Kalinowski:
Predicting IMDb Rating of TV Series with Deep Learning: The Case of Arrow. SBSI 2022: 9:1-9:6 - [i1]Anna Luiza Gomes, Getúlio Vianna, Tatiana Escovedo, Marcos Kalinowski:
Predicting IMDb Rating of TV Series with Deep Learning: The Case of Arrow. CoRR abs/2208.13302 (2022) - 2021
- [c11]Hugo Villamizar, Tatiana Escovedo, Marcos Kalinowski:
Requirements Engineering for Machine Learning: A Systematic Mapping Study. SEAA 2021: 29-36 - [c10]Ney Barchilon, Tatiana Escovedo:
Machine Learning Applied to the INSS Benefit Request. SBSI 2021: 6:1-6:8 - [c9]Marcio Afonso, Tatiana Escovedo:
Clusters of Brazilian municipalities and the relationship with their fiscal management. SBSI 2021: 8:1-8:8 - [c8]José Douglas Nascimento, Tatiana Escovedo:
Construction of Mortality Tables using LSTM Neural Networks. SBSI 2021: 52:1-52:9 - [d1]Hugo Villamizar
Materials: Requirements Engineering for Machine Learning: A Systematic Mapping Study. Zenodo, 2021 - 2020
- [j4]Tatiana Escovedo
Neuroevolutionary learning in nonstationary environments. Appl. Intell. 50(5): 1590-1608 (2020)
2010 – 2019
- 2018
- [j3]Tatiana Escovedo
DetectA: abrupt concept drift detection in non-stationary environments. Appl. Soft Comput. 62: 119-133 (2018) - 2015
- [c7]Tatiana Escovedo, Adriano S. Koshiyama, Marley Maria Bernardes Rebuzzi Vellasco, Rubens Nascimento Melo, André Vargas Abs da Cruz:
A2D2: A pre-event abrupt drift detection. IJCNN 2015: 1-8 - 2014
- [c6]Adriano S. Koshiyama, Tatiana Escovedo
GPFIS-Control: A fuzzy Genetic model for Control tasks. FUZZ-IEEE 2014: 1953-1959 - [c5]Tatiana Escovedo, André Vargas Abs da Cruz, Adriano S. Koshiyama, Rubens Nascimento Melo, Marley Maria Bernardes Rebuzzi Vellasco:
NEVE++: A neuro-evolutionary unlimited ensemble for adaptive learning. IJCNN 2014: 3331-3338 - 2013
- [j2]Tatiana Escovedo
Learning under Concept Drift using a Neuro-Evolutionary Ensemble. Int. J. Comput. Intell. Appl. 12(4) (2013) - [c4]Adriano S. Koshiyama, Tatiana Escovedo, Douglas Mota Dias, Marley M. B. R. Vellasco, Ricardo Tanscheit
GPF-CLASS: A Genetic Fuzzy model for classification. IEEE Congress on Evolutionary Computation 2013: 3275-3282 - [c3]Tatiana Escovedo
NEVE: A Neuro-Evolutionary Ensemble for Adaptive Learning. AIAI 2013: 636-645 - [c2]Tatiana Escovedo, André Vargas Abs da Cruz, Marley Maria Bernardes Rebuzzi Vellasco, Adriano S. Koshiyama:
Using ensembles for adaptive learning: A comparative approach. IJCNN 2013: 1-7 - 2012
- [j1]Adriano S. Koshiyama, Tatiana Escovedo, Douglas Mota Dias, Marley Maria Bernardes Rebuzzi Vellasco, Marco Aurélio Cavalcanti Pacheco:
Combining Forecasts: A Genetic Programming Approach. Int. J. Nat. Comput. Res. 3(3): 41-58 (2012)
2000 – 2009
- 2009
- [c1]Elaine Alves de Carvalho, Tatiana Escovedo, Rubens N. Melo:
Using Business Processes in System Requirements Definition. SEW 2009: 125-130
Coauthor Index
aka: Adriano Soares Koshiyama
aka: Marley Maria Bernardes Rebuzzi Vellasco
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last updated on 2024-10-23 20:30 CEST by the dblp team
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