Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Escovedo, Tatiana"'
Autor:
Alves, Antonio Pedro Santos, Kalinowski, Marcos, Mendez, Daniel, Villamizar, Hugo, Azevedo, Kelly, Escovedo, Tatiana, Lopes, Helio
[Context] In Brazil, 41% of companies use machine learning (ML) to some extent. However, several challenges have been reported when engineering ML-enabled systems, including unrealistic customer expectations and vagueness in ML problem specifications
Externí odkaz:
http://arxiv.org/abs/2407.18977
Autor:
Kalinowski, Marcos, Mendez, Daniel, Giray, Görkem, Alves, Antonio Pedro Santos, Azevedo, Kelly, Escovedo, Tatiana, Villamizar, Hugo, Lopes, Helio, Baldassarre, Teresa, Wagner, Stefan, Biffl, Stefan, Musil, Jürgen, Felderer, Michael, Lavesson, Niklas, Gorschek, Tony
Context: Machine learning (ML)-enabled systems are being increasingly adopted by companies aiming to enhance their products and operational processes. Objective: This paper aims to deliver a comprehensive overview of the current status quo of enginee
Externí odkaz:
http://arxiv.org/abs/2406.04359
Autor:
Cabral, Raphael, Kalinowski, Marcos, Baldassarre, Maria Teresa, Villamizar, Hugo, Escovedo, Tatiana, Lopes, Hélio
[Context] Applying design principles has long been acknowledged as beneficial for understanding and maintainability in traditional software projects. These benefits may similarly hold for Machine Learning (ML) projects, which involve iterative experi
Externí odkaz:
http://arxiv.org/abs/2402.05337
Autor:
Zimelewicz, Eduardo, Kalinowski, Marcos, Mendez, Daniel, Giray, Görkem, Alves, Antonio Pedro Santos, Lavesson, Niklas, Azevedo, Kelly, Villamizar, Hugo, Escovedo, Tatiana, Lopes, Helio, Biffl, Stefan, Musil, Juergen, Felderer, Michael, Wagner, Stefan, Baldassarre, Teresa, Gorschek, Tony
[Context] Systems incorporating Machine Learning (ML) models, often called ML-enabled systems, have become commonplace. However, empirical evidence on how ML-enabled systems are engineered in practice is still limited, especially for activities surro
Externí odkaz:
http://arxiv.org/abs/2402.05333
Autor:
Alves, Antonio Pedro Santos, Kalinowski, Marcos, Giray, Görkem, Mendez, Daniel, Lavesson, Niklas, Azevedo, Kelly, Villamizar, Hugo, Escovedo, Tatiana, Lopes, Helio, Biffl, Stefan, Musil, Jürgen, Felderer, Michael, Wagner, Stefan, Baldassarre, Teresa, Gorschek, Tony
Systems that use Machine Learning (ML) have become commonplace for companies that want to improve their products and processes. Literature suggests that Requirements Engineering (RE) can help address many problems when engineering ML-enabled systems.
Externí odkaz:
http://arxiv.org/abs/2310.06726
Publikováno v:
XVIII Brazilian Symposium on Information Systems 2022
Context: The number of TV series offered nowadays is very high. Due to its large amount, many series are canceled due to a lack of originality that generates a low audience. Problem: Having a decision support system that can show why some shows are a
Externí odkaz:
http://arxiv.org/abs/2208.13302
Publikováno v:
In Applied Soft Computing Journal January 2018 62:119-133
Exploratory Analysis for the Article "Machine Learning Applied to the INSS Benefit Request", published in SBSI 2021
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2659::6592f5f315e637b388eb9488380f73ed
https://zenodo.org/record/5517490
https://zenodo.org/record/5517490