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Journal Articles
- 2024
[j6]Sahra K. G. Silva
, Cléber Gimenez Corrêa, Silvio Ricardo Rodrigues Sanches, Marcelo de S. Lauretto, Fátima L. S. Nunes:
Assessing Depth Perception in Virtual Environments: A Comprehensive Framework. J. Interact. Syst. 15(1): 104-117 (2024)- [j5]Higor Amario de Souza, Marcelo de Souza Lauretto, Fabio Kon, Marcos Lordello Chaim:
Understanding the use of spectrum-based fault localization. J. Softw. Evol. Process. 36(6) (2024) - 2022
- [j4]Miguel G. R. Miguel, Rafael P. Waissman, Marcelo de S. Lauretto, Julio Michael Stern:
Haphazard Intentional Sampling in Survey and Allocation Studies on COVID-19 Prevalence and Vaccine Efficacy. Entropy 24(2): 225 (2022) - 2016
- [j3]Luciano Antônio Digiampietri, Marcelo de Souza Lauretto, Fábio Nakano:
Estratégia de Análise Quantitativa para Revisão de Pré-requisitos em uma Matriz Curricular do Curso de Bacharelado em Sistemas de Informação. Braz. J. Inf. Syst. 9(2) (2016) - 2015
- [j2]Fátima L. S. Nunes, Márcio Eduardo Delamaro, Vagner Mendonça Gonçalves, Marcelo de Souza Lauretto:
CBIR Based Testing Oracles: An Experimental Evaluation of Similarity Functions. Int. J. Softw. Eng. Knowl. Eng. 25(8): 1271-1306 (2015) - 2014
- [j1]Denise Gasques Bastos, Patricia Santos Nascimento, Marcelo de Souza Lauretto:
Análise Empírica de Desempenho de Quatro Métodos de Seleção de Características para Random Forests. Braz. J. Inf. Syst. 7(2): 25-47 (2014)
Conference and Workshop Papers
- 2022
- [c8]Sahra K. G. Silva, Cléber Gimenez Corrêa, Marcelo de S. Lauretto, Fátima L. S. Nunes:
A framework for evaluating depth perception in stereoscopic virtual environments. SVR 2022: 105-114 - 2021
- [c7]Breno Nunes, Tiago Colliri, Marcelo de S. Lauretto, Weiguang Liu, Liang Zhao:
Anomaly Detection in Brazilian Federal Government Purchase Cards Through Unsupervised Learning Techniques. BRACIS (2) 2021: 19-32 - 2017
- [c6]Paulo Santos, Karina Valdivia Delgado, Marcelo de S. Lauretto, Márcio Moretto Ribeiro:
Revisão Sistemática da Literatura sobre ranking de Relacionamentos na Web Semântica. SBSI 2017: 32-39 - 2013
- [c5]Denise Gasques Bastos, Patricia Santos Nascimento, Marcelo de S. Lauretto:
Proposta e Análise de Desempenho de Dois Métodos de Seleção de Características para Random Forests. SBSI 2013: 49-60 - [c4]Melina Brilhadori, Marcelo de S. Lauretto:
Estudo comparativo entre algoritmos de árvores de classificação e máquinas de vetores suporte baseados em ensembles de classificadores. SBSI 2013: 97-108 - [c3]Bárbara B. C. Silva, Marcelo de S. Lauretto, Pablo M. Andrade, Luciana Araújo:
Avaliação de uma Abordagem de Aprendizado Supervisionado para Operações no Mercado de Ações. SBSI 2013: 109-120 - [c2]Cláudio Frizzarini, Marcelo de S. Lauretto:
Proposta de um Algoritmo para Indução de Árvores de Classificação para Dados Desbalanceados. SBSI 2013: 722-733 - 2005
- [c1]Marcelo de S. Lauretto, Julio Michael Stern:
Testing Significance in Bayesian Classifiers. LAPTEC 2005: 34-41
Informal and Other Publications
- 2020
- [i2]Julio Michael Stern, Carlos Alberto De Bragança Pereira, Celma de Oliveira Ribeiro, Cibele Dunder, Fábio Nakano, Marcelo de S. Lauretto:
Otimizacao e Processos Estocasticos Aplicados a Economia e Financas. CoRR abs/2005.13459 (2020) - 2013
- [i1]Marcelo de S. Lauretto, Bárbara B. C. Silva, Pablo M. Andrade:
Evaluation of a Supervised Learning Approach for Stock Market Operations. CoRR abs/1301.4944 (2013)
Coauthor Index
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