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Ricardo Cerri
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2020 – today
- 2024
- [j23]Thiago Zafalon Miranda, Diorge Brognara Sardinha, Ferrante Neri
, Márcio P. Basgalupp, Ricardo Cerri:
A Grammar-based multi-objective neuroevolutionary algorithm to generate fully convolutional networks with novel topologies. Appl. Soft Comput. 149(Part A): 110967 (2024) - [j22]Cleber A. C. F. da Silva, Daniel Carneiro Rosa, Péricles B. C. de Miranda, Tapas Si, Ricardo Cerri, Márcio P. Basgalupp:
Automated CNN optimization using multi-objective grammatical evolution. Appl. Soft Comput. 151: 111124 (2024) - [j21]Rafael Gomes Mantovani, Tomás Horváth, André L. D. Rossi, Ricardo Cerri, Sylvio Barbon Junior, Joaquin Vanschoren
Better trees: an empirical study on hyperparameter tuning of classification decision tree induction algorithms. Data Min. Knowl. Discov. 38(3): 1364-1416 (2024) - [c48]Silvana C. S. Cardoso, Douglas Silva Domingues, Alexandre Rossi Paschoal, Carlos N. Fischer, Ricardo Cerri:
Classification of LTR Retrotransposons via Interaction Prediction. CIBCB 2024: 1-8 - [c47]Breno O. Funicheli, Claudio Brondani, Rosana P. Vianello, Ricardo Cerri:
Ensemble Methods for Selecting Single Nucleotide Polymorphisms Associated to Rice Phenotypes. IJCNN 2024: 1-8 - [c46]Pedro Ilidio, Ricardo Cerri, Celine Vens, Felipe Kenji Nakano:
Deep forests with tree-embeddings and label imputation for weak-label learning. IJCNN 2024: 1-8 - [c45]Pedro Ilidio
Fast Bipartite Forests for Semi-supervised Interaction Prediction. SAC 2024: 979-986 - 2023
- [j20]Aline Marques Del Valle, Rafael Gomes Mantovani, Ricardo Cerri:
A systematic literature review on AutoML for multi-target learning tasks. Artif. Intell. Rev. 56(S2): 2013-2052 (2023) - [j19]Joel D. Costa, Elaine R. Faria, Jonathan de Andrade Silva, João Gama, Ricardo Cerri
Novelty detection for multi-label stream classification under extreme verification latency. Appl. Soft Comput. 141: 110265 (2023) - [j18]Mauri Ferrandin
Multi-label classification via closed frequent labelsets and label taxonomies. Soft Comput. 27(13): 8627-8660 (2023) - [c44]Elaine Cecília Gatto
Community Detection for Multi-label Classification. BRACIS (1) 2023: 78-93 - [c43]Rodney Renato de Souza Silva, Ricardo Cerri
Constructive Machine Learning and Hierarchical Multi-label Classification for Molecules Design. BRACIS (2) 2023: 276-290 - [c42]Aline Marques Del Valle, Rafael Gomes Mantovani, Ricardo Cerri:
AutoMMLC: An Automated and Multi-objective Method for Multi-label Classification. BRACIS (2) 2023: 291-306 - [c41]Bruna Zamith Santos, Balbina Maria Araujo Soriano, Marcelo Gonçalves Narciso, Diego Furtado Silva, Ricardo Cerri:
A New Time Series Framework for Forest Fire Risk Forecasting and Classification. IJCNN 2023: 1-8 - [c40]André Hallwas Ribeiro Alves
Semi-Supervised Hybrid Predictive Bi-Clustering Trees for Drug-Target Interaction Prediction. SAC 2023: 1163-1170 - 2022
- [c39]Thiago Zafalon Miranda, Diorge Brognara Sardinha, Márcio Porto Basgalupp
A new grammatical evolution method for generating deep convolutional neural networks with novel topologies. GECCO Companion 2022: 663-666 - [c38]Ricardo Cerri, Elaine R. Faria, João Gama:
An Algorithm Adaptation Method for Multi-Label Stream Classification using Self-Organizing Maps. ICMLA 2022: 1071-1076 - [c37]André Hallwas Ribeiro Alves
A Two-step Model for Drug-Target Interaction Prediction with Predictive Bi-Clustering Trees and XGBoost. IJCNN 2022: 1-8 - 2021
- [j17]Thiago Zafalon Miranda, Diorge Brognara Sardinha, Ricardo Cerri:
Preventing the generation of inconsistent sets of crisp classification rules. Expert Syst. Appl. 165: 113811 (2021) - [j16]Márcio P. Basgalupp
Beyond global and local multi-target learning. Inf. Sci. 579: 508-524 (2021) - [j15]Luíza Zuvanov
The experience of teaching introductory programming skills to bioscientists in Brazil. PLoS Comput. Biol. 17(11) (2021) - [c36]Luan V. M. da Silva, Ricardo Cerri
Feature Selection for Hierarchical Multi-label Classification. IDA 2021: 196-208 - [c35]Brendon Gouveia Cambuí, Rafael Gomes Mantovani, Ricardo Cerri:
Exploring Autoencoders for Feature Extraction in Multi-Target Classification. IJCNN 2021: 1-8 - [c34]Elaine Cecília Gatto
Exploring Label Correlations for Partitioning the Label Space in Multi-label Classification. IJCNN 2021: 1-8 - [c33]Ricardo Cerri, Joel David Costa Júnior, Elaine R. Faria
A new self-organizing map based algorithm for multi-label stream classification. SAC 2021: 418-426 - 2020
- [j14]Saulo Martiello Mastelini
DSTARS: A multi-target deep structure for tracking asynchronous regressor stacking. Appl. Soft Comput. 91: 106215 (2020) - [j13]Felipe Kenji Nakano
Active learning for hierarchical multi-label classification. Data Min. Knowl. Discov. 34(5): 1496-1530 (2020) - [c32]Thiago Zafalon Miranda, Diorge Brognara Sardinha, Márcio Porto Basgalupp
Generation of consistent sets of multi-label classification rules with a multi-objective evolutionary algorithm. GECCO Companion 2020: 143-144 - [c31]Bruna Zamith Santos
Predictive Bi-clustering Trees for Hierarchical Multi-label Classification. ECML/PKDD (3) 2020: 701-718 - [e2]Ricardo Cerri
Intelligent Systems - 9th Brazilian Conference, BRACIS 2020, Rio Grande, Brazil, October 20-23, 2020, Proceedings, Part I. Lecture Notes in Computer Science 12319, Springer 2020, ISBN 978-3-030-61376-1 [contents] - [e1]Ricardo Cerri
Intelligent Systems - 9th Brazilian Conference, BRACIS 2020, Rio Grande, Brazil, October 20-23, 2020, Proceedings, Part II. Lecture Notes in Computer Science 12320, Springer 2020, ISBN 978-3-030-61379-2 [contents] - [i4]Thiago Zafalon Miranda, Diorge Brognara Sardinha, Márcio Porto Basgalupp, Yaochu Jin, Ricardo Cerri:
Generation of Consistent Sets of Multi-Label Classification Rules with a Multi-Objective Evolutionary Algorithm. CoRR abs/2003.12526 (2020) - [i3]Ricardo Cerri, Joel David Costa Júnior, Elaine Ribeiro de Faria Paiva, João Manuel Portela da Gama:
Multi-label Stream Classification with Self-Organizing Maps. CoRR abs/2004.09397 (2020)
2010 – 2019
- 2019
- [j12]Ricardo Cerri
Inducing Hierarchical Multi-label Classification rules with Genetic Algorithms. Appl. Soft Comput. 77: 584-604 (2019) - [j11]Saulo Martiello Mastelini
Multi-Output Tree Chaining: An Interpretative Modelling and Lightweight Multi-Target Approach. J. Signal Process. Syst. 91(2): 191-215 (2019) - [c30]Felipe Kenji Nakano, Ricardo Cerri:
Hierarchical Classification of Transposable Elements. BNAIC/BENELEARN 2019 - [c29]Joel D. Costa Júnior, Elaine Ribeiro de Faria
Novelty Detection for Multi-Label Stream Classification. BRACIS 2019: 144-149 - [c28]Gean Trindade Pereira, Paulo Henrique Ribeiro Gabriel
Hierarchical Classification of Transposable Elements with a Weighted Genetic Algorithm. EPIA (1) 2019: 737-749 - [c27]Gean Trindade Pereira, Paulo Henrique Ribeiro Gabriel
A lexicographic genetic algorithm for hierarchical classification rule induction. GECCO 2019: 846-854 - [c26]Joel D. Costa Júnior, Elaine R. Faria
Pruned Sets for Multi-Label Stream Classification without True Labels. IJCNN 2019: 1-8 - [i2]Thiago Zafalon Miranda, Diorge Brognara Sardinha, Ricardo Cerri:
Preventing the Generation of Inconsistent Sets of Classification Rules. CoRR abs/1908.09652 (2019) - 2018
- [j10]Alex Marino Gonçalves de Almeida
Applying multi-label techniques in emotion identification of short texts. Neurocomputing 320: 35-46 (2018) - [j9]Angelo Brayner, Maristela Holanda, Ricardo Cerri:
frontmatter. J. Inf. Data Manag. 9(2): 107 (2018) - [j8]Gean Trindade Pereira, Ricardo Cerri:
Hierarchical and Non-Hierarchical Classification of Transposable Elements with a Genetic Algorithm. J. Inf. Data Manag. 9(2): 163-178 (2018) - [j7]Leander Schietgat, Celine Vens
A machine learning based framework to identify and classify long terminal repeat retrotransposons. PLoS Comput. Biol. 14(4) (2018) - [c25]Bruna Zamith Santos
Strategies for Selection of Positive and Negative Instances in the Hierarchical Classification of Transposable Elements. BRACIS 2018: 420-425 - [c24]Gean Trindade Pereira, Bruna Zamith Santos
A Genetic Algorithm for Transposable Elements Hierarchical Classification Rule Induction. CEC 2018: 1-8 - [c23]Jonatas Wehrmann, Ricardo Cerri, Rodrigo C. Barros:
Hierarchical Multi-Label Classification Networks. ICML 2018: 5225-5234 - [c22]Ricardo Cerri
Multi-label Feature Selection Techniques for Hierarchical Multi-label Protein Function Prediction. IJCNN 2018: 1-7 - [c21]Felipe Kenji Nakano, Saulo Martiello Mastelini, Sylvio Barbon
Improving Hierarchical Classification of Transposable Elements using Deep Neural Networks. IJCNN 2018: 1-8 - [i1]Rafael Gomes Mantovani
An empirical study on hyperparameter tuning of decision trees. CoRR abs/1812.02207 (2018) - 2017
- [c20]Saulo Martiello Mastelini, Everton Jose Santana
DSTARS: A Multi-target Deep Structure for Tracking Asynchronous Regressor Stack. BRACIS 2017: 19-24 - [c19]Felipe Kenji Nakano, Saulo Martiello Mastelini, Sylvio Barbon
Stacking Methods for Hierarchical Classification. ICMLA 2017: 289-296 - [c18]Iuri Bonna M. de Abreu, Rafael Gomes Mantovani
Incorporating instance correlations in multi-label classification via label-space. IJCNN 2017: 581-588 - [c17]Felipe Kenji Nakano, Walter José G. S. Pinto, Gisele Lobo Pappa, Ricardo Cerri
Top-down strategies for hierarchical classification of transposable elements with neural networks. IJCNN 2017: 2539-2546 - [c16]Gustavo G. Colombini, Iuri Bonna M. de Abreu, Ricardo Cerri
A self-organizing map-based method for multi-label classification. IJCNN 2017: 4291-4298 - [c15]Jonatas Wehrmann
Hierarchical multi-label classification with chained neural networks. SAC 2017: 790-795 - 2016
- [j6]Ricardo Cerri
Reduction strategies for hierarchical multi-label classification in protein function prediction. BMC Bioinform. 17: 373 (2016) - [c14]Rafael Gomes Mantovani
Hyper-Parameter Tuning of a Decision Tree Induction Algorithm. BRACIS 2016: 37-42 - 2015
- [j5]Carlos N. Fischer
Learning HMMs for nucleotide sequences from amino acid alignments. Bioinform. 31(11): 1836-1838 (2015) - [j4]Ricardo Cerri
An Extensive Evaluation of Decision Tree-Based Hierarchical Multilabel Classification Methods and Performance Measures. Comput. Intell. 31(1): 1-46 (2015) - [c13]Ricardo Cerri
Hierarchical classification of Gene Ontology-based protein functions with neural networks. IJCNN 2015: 1-8 - 2014
- [j3]Rodrigo C. Barros
A framework for bottom-up induction of oblique decision trees. Neurocomputing 135: 3-12 (2014) - [j2]Ricardo Cerri
Hierarchical multi-label classification using local neural networks. J. Comput. Syst. Sci. 80(1): 39-56 (2014) - [c12]Ricardo Cerri
Evolving relational hierarchical classification rules for predicting gene ontology-based protein functions. GECCO (Companion) 2014: 1279-1286 - 2013
- [b1]Ricardo Cerri:
Neural networks and genetic algorithms for hierarchical multi-label classification. University of São Paulo, Brazil, 2013 - [c11]Ricardo Cerri
Neural Networks for Hierarchical Classification of G-Protein Coupled Receptors. BRACIS 2013: 125-130 - [c10]Ricardo Cerri
A grammatical evolution algorithm for generation of Hierarchical Multi-Label Classification rules. IEEE Congress on Evolutionary Computation 2013: 454-461 - [c9]Rodrigo C. Barros
A grammatical evolution approach for software effort estimation. GECCO 2013: 1413-1420 - [c8]Rodrigo C. Barros
Probabilistic Clustering for Hierarchical Multi-Label Classification of Protein Functions. ECML/PKDD (2) 2013: 385-400 - 2012
- [c7]Ricardo Cerri
A genetic algorithm for Hierarchical Multi-Label Classification. SAC 2012: 250-255 - 2011
- [j1]Ricardo Cerri
Adapting non-hierarchical multilabel classification methods for hierarchical multilabel classification. Intell. Data Anal. 15(6): 861-887 (2011) - [c6]Ricardo Cerri
Hierarchical multi-label classification for protein function prediction: A local approach based on neural networks. ISDA 2011: 337-343 - [c5]Rodrigo C. Barros
A bottom-up oblique decision tree induction algorithm. ISDA 2011: 450-456 - [c4]Ricardo Cerri
Hierarchical Multilabel Protein Function Prediction Using Local Neural Networks. BSB 2011: 10-17 - 2010
- [c3]Ricardo Cerri
New top-down methods using SVMs for Hierarchical Multilabel Classification problems. IJCNN 2010: 1-8 - [c2]Ricardo Cerri
Hierarchical Multilabel Classification Using Top-Down Label Combination and Artificial Neural Networks. SBRN 2010: 253-258
2000 – 2009
- 2009
- [c1]Ricardo Cerri
Comparing Methods for Multilabel Classification of Proteins Using Machine Learning Techniques. BSB 2009: 109-120
Coauthor Index
Rodrigo C. Barros
aka: Rodrigo Coelho Barros
aka: Rodrigo Coelho Barros
André C. P. L. F. de Carvalho
aka: André Carlos Ponce de Leon Ferreira de Carvalho
aka: André Carlos Ponce de Leon Ferreira de Carvalho
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