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Renato Vimieiro
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2020 – today
- 2025
- [j7]Renato Vimieiro, Juliana Barcellos Mattos, Paulo S. G. de Mattos Neto:
EsmamDS: A more diverse exceptional survival model mining approach. Inf. Sci. 690: 121549 (2025) - 2024
- [i2]Paulo Coelho, Raul Araju, Luís Ramos, Samir Saliba, Renato Vimieiro:
Graph Neural Alchemist: An innovative fully modular architecture for time series-to-graph classification. CoRR abs/2410.09307 (2024) - 2022
- [j6]Pedro Paulo Valadares Brum, Matheus Cândido Teixeira, Renato Vimieiro, Eric Araújo, Wagner Meira Jr., Gisele Lobo Pappa:
Political polarization on Twitter during the COVID-19 pandemic: a case study in Brazil. Soc. Netw. Anal. Min. 12(1): 140 (2022) - [c11]Cinthia Mikaela de Souza, Magali R. G. Meireles, Renato Vimieiro:
A multi-view extractive text summarization approach for long scientific articles. IJCNN 2022: 1-8 - 2021
- [c10]Luís Gonçalves, Renato Vimieiro:
Approaching authorship attribution as a multi-view supervised learning task. IJCNN 2021: 1-8 - [i1]Juliana Barcellos Mattos, Paulo S. G. de Mattos Neto, Renato Vimieiro:
EsmamDS: A more diverse exceptional survival model mining approach. CoRR abs/2109.02610 (2021) - 2020
- [c9]Juliana Barcellos Mattos, Eraylson G. Silva, Paulo S. G. de Mattos Neto, Renato Vimieiro:
Exceptional Survival Model Mining. BRACIS (2) 2020: 307-321
2010 – 2019
- 2019
- [c8]Tarcísio Lucas, João Gomes, Renato Vimieiro, Ricardo B. C. Prudêncio, Teresa Bernarda Ludermir:
A Multivariate Method for Group Profiling Using Subgroup Discovery. BRACIS 2019: 371-376 - [c7]Andréa B. Duque, Francisco de A. T. de Carvalho, Renato Vimieiro:
A Multiview Clustering Approach for Mining Authorial Affinities in Literary Texts. BRACIS 2019: 818-823 - 2018
- [c6]Vitor de Albuquerque Torreao, Renato Vimieiro:
Effects of Population Initialization on Evolutionary Techniques for Subgroup Discovery in High Dimensional Datasets. BRACIS 2018: 25-30 - [c5]Tarcísio Lucas, Renato Vimieiro, Teresa Bernarda Ludermir:
SSDP+: A Diverse and More Informative Subgroup Discovery Approach for High Dimensional Data. CEC 2018: 1-8 - 2017
- [j5]Tarcísio Lucas, Túlio C. P. B. Silva, Renato Vimieiro, Teresa Bernarda Ludermir:
A new evolutionary algorithm for mining top-k discriminative patterns in high dimensional data. Appl. Soft Comput. 59: 487-499 (2017) - 2016
- [j4]Heloisa H. Milioli, Renato Vimieiro, Inna Tishchenko, Carlos Riveros, Regina Berretta, Pablo Moscato:
Iteratively refining breast cancer intrinsic subtypes in the METABRIC dataset. BioData Min. 9: 2 (2016) - [c4]Tarcisio Pontes, Renato Vimieiro, Teresa Bernarda Ludermir:
SSDP: A Simple Evolutionary Approach for Top-K Discriminative Patterns in High Dimensional Databases. BRACIS 2016: 361-366 - 2014
- [j3]Renato Vimieiro, Pablo Moscato:
A new method for mining disjunctive emerging patterns in high-dimensional datasets using hypergraphs. Inf. Syst. 40: 1-10 (2014) - [j2]Renato Vimieiro, Pablo Moscato:
Disclosed: An efficient depth-first, top-down algorithm for mining disjunctive closed itemsets in high-dimensional data. Inf. Sci. 280: 171-187 (2014) - 2012
- [j1]Renato Vimieiro, Pablo Moscato:
Mining disjunctive minimal generators with TitanicOR. Expert Syst. Appl. 39(9): 8228-8238 (2012)
2000 – 2009
- 2006
- [c3]Mark A. J. Song, Luis E. Zárate, Sérgio M. Dias, Ana Alvarez, Bruno Soares, Bruno M. Nogueira, Renato Vimieiro, Tadeu R. A. Santos, Newton Vieira:
SOPHIANN: A Tool for Extraction Knowledge Rules from ANN Previously Trained A Case Study. SEKE 2006: 631-638 - 2004
- [c2]Luis E. Zárate, Elizabeth Marques Duarte Pereira, Daniel A. Soares, João Paulo D. Silva, Renato Vimieiro, Antônia Sônia Cardoso Diniz:
Optimization of Neural Network's Training Sets via Clustering: Application in Solar Collector Representation. ICEIS (2) 2004: 147-152 - [c1]Luis E. Zárate, Elizabeth Marques Duarte Pereira, João Paulo D. Silva, Renato Vimieiro, Antônia Sônia Cardoso Diniz:
Neural Representation of a Solar Collector with Statistical Optimization of the Training Set. IEA/AIE 2004: 87-96
Coauthor Index
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last updated on 2025-01-09 13:25 CET by the dblp team
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