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2020 – today
- 2024
[j23]Cristina Y. Morimoto
, Aurora Trinidad Ramirez Pozo, Marcílio Carlos Pereira de Souto:
An adaptive evolutionary multi-objective clustering based on the data properties of the base partitions. Expert Syst. Appl. 245: 123102 (2024)- 2023
- [j22]Sofiane Elguendouze, Adel Hafiane, Marcilio C. P. de Souto, Anaïs Halftermeyer:
Explainability in image captioning based on the latent space. Neurocomputing 546: 126319 (2023) - [c56]Carmen Lancho, Marcilio C. P. de Souto, Ana Carolina Lorena, Isaac Martín de Diego:
Complexity-Driven Sampling for Bagging. IDEAL 2023: 15-21 - 2022
- [j21]Cristina Y. Morimoto, Aurora T. R. Pozo, Marcilio C. P. de Souto:
An analysis of the admissibility of the objective functions applied in evolutionary multi-objective clustering. Inf. Sci. 610: 1143-1162 (2022) - [c55]Cristina Y. Morimoto, Aurora T. R. Pozo, Marcílio Carlos Pereira de Souto:
Detecting Nested Structures Through Evolutionary Multi-objective Clustering. EvoApplications 2022: 369-385 - [c54]Sofiane Elguendouze, Marcilio C. P. de Souto, Adel Hafiane, Anaïs Lefeuvre-Halftermeyer:
Towards Explainable Deep Learning for Image Captioning through Representation Space Perturbation. IJCNN 2022: 1-8 - [c53]Mathieu Guilbert, Christel Vrain, Thi-Bich-Hanh Dao, Marcilio C. P. de Souto:
Anchored Constrained Clustering Ensemble. IJCNN 2022: 1-8 - [i4]Cristina Y. Morimoto, Aurora T. R. Pozo, Marcílio Carlos Pereira de Souto:
An Analysis of the Admissibility of the Objective Functions Applied in Evolutionary Multi-objective Clustering. CoRR abs/2206.09483 (2022) - 2021
- [j20]Victor H. Barella, Luís Paulo F. Garcia, Marcilio C. P. de Souto, Ana Carolina Lorena, André C. P. L. F. de Carvalho:
Assessing the data complexity of imbalanced datasets. Inf. Sci. 553: 83-109 (2021) - [c52]Adriano Kultzak, Cristina Y. Morimoto, Aurora T. R. Pozo, Marcilio C. P. de Souto:
Multi-objective Clustering: A Data-Driven Analysis of MOCLE, MOCK and Δ-MOCK. ICONIP (5) 2021: 46-54 - [c51]Luiz Henrique dos Santos Fernandes, Marcilio C. P. de Souto, Ana Carolina Lorena:
Evaluating Data Characterization Measures for Clustering Problems in Meta-learning. ICONIP (1) 2021: 621-632 - [c50]Hério Sousa, Marcilio C. P. de Souto, Reginaldo Massanobu Kuroshu, Ana Carolina Lorena:
Automatic recovering the number k of clusters in the data by active query selection. SAC 2021: 1021-1029 - [i3]Adriano Kultzak, Cristina Y. Morimoto, Aurora T. R. Pozo, Marcilio C. P. de Souto:
Multi-objective Clustering: A Data-driven Analysis of MOCLE, MOCK and Δ-MOCK. CoRR abs/2110.07521 (2021) - [i2]Cristina Y. Morimoto, Aurora T. R. Pozo, Marcilio C. P. de Souto:
A Survey of Evolutionary Multi-Objective Clustering Approaches. CoRR abs/2110.08100 (2021) - 2020
- [j19]Vanessa Antunes, Tiemi C. Sakata, Katti Faceli, Marcilio C. P. de Souto:
Hybrid strategy for selecting compact set of clustering partitions. Appl. Soft Comput. 87: 105971 (2020)
2010 – 2019
- 2019
- [j18]Ana Carolina Lorena, Luís Paulo F. Garcia, Jens Lehmann, Marcílio Carlos Pereira de Souto, Tin Kam Ho:
How Complex Is Your Classification Problem?: A Survey on Measuring Classification Complexity. ACM Comput. Surv. 52(5): 107:1-107:34 (2019) - 2018
- [c49]Luís Paulo F. Garcia, Ana Carolina Lorena, Marcilio C. P. de Souto, Tin Kam Ho:
Classifier Recommendation Using Data Complexity Measures. ICPR 2018: 874-879 - [c48]Victor H. Barella, Luís Paulo F. Garcia, Marcilio C. P. de Souto, Ana Carolina Lorena, André C. P. L. F. de Carvalho:
Data Complexity Measures for Imbalanced Classification Tasks. IJCNN 2018: 1-8 - [i1]Ana Carolina Lorena, Luís Paulo F. Garcia, Jens Lehmann, Marcilio C. P. de Souto, Tin Kam Ho:
How Complex is your classification problem? A survey on measuring classification complexity. CoRR abs/1808.03591 (2018) - 2017
- [c47]Bruno A. Pimentel, Marcilio C. P. de Souto, Renata M. C. R. de Souza:
Interpreting multivariate membership degrees of fuzzy clustering methods: A strategy. IJCNN 2017: 2800-2804 - 2015
- [j17]Marcílio Carlos Pereira de Souto, Pablo A. Jaskowiak, Ivan G. Costa:
Impact of missing data imputation methods on gene expression clustering and classification. BMC Bioinform. 16: 64:1-64:9 (2015) - [c46]Ana Carolina Lorena, Marcílio Carlos Pereira de Souto:
On Measuring the Complexity of Classification Problems. ICONIP (1) 2015: 158-167 - [c45]Jane Piantoni, Katti Faceli, Tiemi C. Sakata, Julio C. Pereira, Marcílio Carlos Pereira de Souto:
Impact of Base Partitions on Multi-objective and Traditional Ensemble Clustering Algorithms. ICONIP (1) 2015: 696-704 - 2014
- [c44]Eduardo G. Gusmão, Marcilio C. P. de Souto:
Issues on sampling negative examples for predicting prokaryotic promoters. IJCNN 2014: 494-501 - [c43]Katti Faceli, Tiemi C. Sakata, André Carlos Ponce de Leon Ferreira de Carvalho, Marcílio Carlos Pereira de Souto:
PVis - Partitions' visualizer: Extracting knowledge by visualizing a collection of partitions. IJCNN 2014: 3056-3061 - 2013
- [j16]Marcilio C. P. de Souto, Maricel G. Kann:
Guest Editorial for Special Section on BSB 2012. IEEE ACM Trans. Comput. Biol. Bioinform. 10(4): 817-818 (2013) - 2012
- [j15]Teresa Bernarda Ludermir, Marcílio Carlos Pereira de Souto, Marley M. B. R. Vellasco:
Automatic parameters selection in machine learning. Neurocomputing 75(1): 1-2 (2012) - [j14]Ana Carolina Lorena, Ivan G. Costa, Newton Spolaôr, Marcílio Carlos Pereira de Souto:
Analysis of complexity indices for classification problems: Cancer gene expression data. Neurocomputing 75(1): 33-42 (2012) - [c42]Marcilio C. P. de Souto, André L. V. Coelho, Katti Faceli, Tiemi C. Sakata, Viviane Bonadia, Ivan G. Costa:
A Comparison of External Clustering Evaluation Indices in the Context of Imbalanced Data Sets. SBRN 2012: 49-54 - [e4]Marcílio Carlos Pereira de Souto, Maricel G. Kann:
Advances in Bioinformatics and Computational Biology - 7th Brazilian Symposium on Bioinformatics, BSB 2012, Campo Grande, Brazil, August 15-17, 2012. Proceedings. Lecture Notes in Computer Science 7409, Springer 2012, ISBN 978-3-642-31926-6 [contents] - 2011
- [c41]Marcilio C. P. de Souto, José Carlos Martins Oliveira, Teresa Bernarda Ludermir:
A tool to implement probabilistic automata in RAM-based neural networks. IJCNN 2011: 1054-1060 - [p1]Ricardo Bastos Cavalcante Prudêncio, Marcilio C. P. de Souto, Teresa Bernarda Ludermir:
Selecting Machine Learning Algorithms Using the Ranking Meta-Learning Approach. Meta-Learning in Computational Intelligence 2011: 225-243 - 2010
- [j13]Marley M. B. R. Vellasco, Marcílio Carlos Pereira de Souto, André Carlos Ponce de Leon Ferreira de Carvalho:
Special issue for the SBRN Guest Editorial. Neurocomputing 73(16-18): 2797-2798 (2010) - [j12]Katti Faceli, Tiemi C. Sakata, Marcílio Carlos Pereira de Souto, André Carlos Ponce de Leon Ferreira de Carvalho:
Partitions selection strategy for set of clustering solutions. Neurocomputing 73(16-18): 2809-2819 (2010) - [c40]Marcílio Carlos Pereira de Souto, Ana Carolina Lorena, Newton Spolaôr, Ivan Gesteira Costa:
Complexity measures of supervised classifications tasks: A case study for cancer gene expression data. IJCNN 2010: 1-7 - [c39]Tiemi C. Sakata, Katti Faceli, Marcílio Carlos Pereira de Souto, André Carlos Ponce de Leon Ferreira de Carvalho:
Improvements in the Partitions Selection Strategy for Set of Clustering Solutions. SBRN 2010: 49-54 - [c38]Ana Carolina Lorena, Newton Spolaôr, Ivan G. Costa, Marcilio C. P. de Souto:
On the Complexity of Gene Marker Selection. SBRN 2010: 85-90
2000 – 2009
- 2009
- [j11]Teresa Bernarda Ludermir, Marcílio Carlos Pereira de Souto, Wilson Rosa de Oliveira:
On a hybrid weightless neural system. Int. J. Bio Inspired Comput. 1(1/2): 93-104 (2009) - [j10]Katti Faceli, Marcílio Carlos Pereira de Souto, Daniel S. A. de Araujo, André Carlos Ponce de Leon Ferreira de Carvalho:
Multi-objective clustering ensemble for gene expression data analysis. Neurocomputing 72(13-15): 2763-2774 (2009) - [c37]Diogo F. de Oliveira, Anne M. P. Canuto, Marcílio Carlos Pereira de Souto:
The diversity/accuracy dilemma: An empirical analysis in the context of heterogeneous ensembles. IEEE Congress on Evolutionary Computation 2009: 939-946 - [c36]André C. A. Nascimento, Ricardo Bastos Cavalcante Prudêncio, Marcílio Carlos Pereira de Souto, Ivan G. Costa:
Mining Rules for the Automatic Selection Process of Clustering Methods Applied to Cancer Gene Expression Data. ICANN (2) 2009: 20-29 - [c35]Diogo F. de Oliveira, Anne M. P. Canuto, Marcílio Carlos Pereira de Souto:
Use of multi-objective genetic algorithms to investigate the diversity/accuracy dilemma in heterogeneous ensembles. IJCNN 2009: 2339-2346 - [c34]Ivan G. Costa, Ana Carolina Lorena, Liciana R. M. P. y Peres, Marcílio Carlos Pereira de Souto:
Using Supervised Complexity Measures in the Analysis of Cancer Gene Expression Data Sets. BSB 2009: 48-59 - 2008
- [j9]Marcílio Carlos Pereira de Souto, Ivan G. Costa, Daniel S. A. de Araujo, Teresa Bernarda Ludermir, Alexander Schliep:
Clustering cancer gene expression data: a comparative study. BMC Bioinform. 9 (2008) - [j8]André Carlos Ponce de Leon Ferreira de Carvalho, Anne M. P. Canuto, Marcílio Carlos Pereira de Souto:
Brazilian Symposium on Neural Networks (SBRN2006). Neurocomputing 71(16-18): 3317 (2008) - [c33]Karliane M. O. Vale, Filipe G. Dias, Anne M. P. Canuto, Marcílio Carlos Pereira de Souto:
A Class-Based Feature Selection Method for Ensemble Systems. HIS 2008: 596-601 - [c32]Ana Carolina Lorena, Ivan G. Costa, Marcílio Carlos Pereira de Souto:
On the Complexity of Gene Expression Classification Data Sets. HIS 2008: 825-830 - [c31]Marcílio Carlos Pereira de Souto, Rodrigo G. F. Soares, Alixandre Santana, Anne M. P. Canuto:
Empirical comparison of Dynamic Classifier Selection methods based on diversity and accuracy for building ensembles. IJCNN 2008: 1480-1487 - [c30]Marcílio Carlos Pereira de Souto, Daniel S. A. de Araujo, Ivan G. Costa, Rodrigo G. F. Soares, Teresa Bernarda Ludermir, Alexander Schliep:
Comparative study on normalization procedures for cluster analysis of gene expression datasets. IJCNN 2008: 2792-2798 - [c29]Marcílio Carlos Pereira de Souto, Ricardo Bastos Cavalcante Prudêncio, Rodrigo G. F. Soares, Daniel S. A. de Araujo, Ivan G. Costa, Teresa Bernarda Ludermir, Alexander Schliep:
Ranking and selecting clustering algorithms using a meta-learning approach. IJCNN 2008: 3729-3735 - [c28]Katti Faceli, Marcílio Carlos Pereira de Souto, André Carlos Ponce de Leon Ferreira de Carvalho:
A Strategyfor the Selection of Solutions of the Pareto Front Approximation in Multi-objective Clustering Approaches. SBRN 2008: 27-32 - [c27]Teresa Bernarda Ludermir, Marcílio Carlos Pereira de Souto, Wilson Rosa de Oliveira:
Weightless Neural Networks: Knowledge-Based Inference System. SBRN 2008: 207-212 - [e3]Marley Maria Bernardes Rebuzzi Vellasco, Marcílio Carlos Pereira de Souto, Jés Jesus Fiais Cerqueira:
10th Brazilian Symposium on Neural Networks (SBRN 2008), Salvador, Bahia, Brazil, October 26-30, 2008. IEEE Computer Society 2008, ISBN 978-0-7695-3361-2 [contents] - 2007
- [j7]Katti Faceli, André Carlos Ponce de Leon Ferreira de Carvalho, Marcílio Carlos Pereira de Souto:
Multi-objective clustering ensemble. Int. J. Hybrid Intell. Syst. 4(3): 145-156 (2007) - [c26]Lucas M. Oliveira, Raul Benites Paradeda, Bruno M. Carvalho, Anne M. P. Canuto, Marcílio Carlos Pereira de Souto:
Particle Detection on Election Microscopy Micrographs Using Multi-Classifier Systems. HIS 2007: 216-221 - [c25]Laura Emmanuella A. Santana, Diogo F. de Oliveira, Anne M. P. Canuto, Marcílio Carlos Pereira de Souto:
A Comparative Analysis of Feature Selection Methods for Ensembles with Different Combination Methods. IJCNN 2007: 643-648 - [c24]Diogo F. de Oliveira, Anne M. P. Canuto, Marcílio Carlos Pereira de Souto:
Investigating the Use of an Evolutionary Agent-based System for Classification Tasks. IJCNN 2007: 1266-1271 - [c23]Diogo F. de Oliveira, Anne M. P. Canuto, Marcilio C. P. de Souto:
Using an Evolutionary Agent-Based System for Classification Tasks. ISDA 2007: 27-32 - [c22]Katti Faceli, André Carlos Ponce de Leon Ferreira de Carvalho, Marcílio Carlos Pereira de Souto:
Multi-Objective Clustering Ensemble with Prior Knowledge. BSB 2007: 34-45 - [c21]Ivan G. Costa, Marcílio Carlos Pereira de Souto, Alexander Schliep:
Validating Gene Clusterings by Selecting Informative Gene Ontology Terms with Mutual Information. BSB 2007: 81-92 - 2006
- [c20]Welbson S. Costa, Mateus S. de Assis, Marcílio Carlos Pereira de Souto:
Extracting Symbolic Rules from Clustering of Gene Expression Data. HIS 2006: 12 - [c19]Katti Faceli, André Carlos Ponce de Leon Ferreira de Carvalho, Marcílio Carlos Pereira de Souto:
Multi-Objective Clustering Ensemble. HIS 2006: 51 - [c18]Marcílio Carlos Pereira de Souto, Valnaide G. Bittencourt, José Alfredo Ferreira Costa:
An Empirical Analysis of Under-Sampling Techniques to Balance a Protein Structural Class Dataset. ICONIP (3) 2006: 21-29 - [c17]Thiago Dutra, Anne M. P. Canuto, Marcílio Carlos Pereira de Souto:
Using Weighted Combination-Based Methods in Ensembles with Different Levels of Diversity. ICONIP (1) 2006: 708-717 - [c16]Rodrigo G. F. Soares, Alixandre Santana, Anne M. P. Canuto, Marcílio Carlos Pereira de Souto:
Using Accuracy and Diversity to Select Classifiers to Build Ensembles. IJCNN 2006: 1310-1316 - [c15]Marcílio Carlos Pereira de Souto, Daniel S. A. de Araujo, Bruno L. C. da Silva:
Cluster Ensemble for Gene Expression Microarray Data: Accuracy and Diversity. IJCNN 2006: 2174-2180 - [c14]Kelly P. da Silva, Meika I. Monteiro, Marcílio Carlos Pereira de Souto:
In silico prediction of promoter sequences of Bacillus species. IJCNN 2006: 2319-2324 - [c13]Alixandre Santana, Rodrigo G. F. Soares, Anne M. P. Canuto, Marcílio Carlos Pereira de Souto:
A Dynamic Classifier Selection Method to Build Ensembles using Accuracy and Diversity. SBRN 2006: 36-41 - [e2]Anne M. P. Canuto, Marcílio Carlos Pereira de Souto, Antônio Carlos Roque-da-Silva:
SBRN 2006, The Ninth Brazilian Symposium on Neural Networks, Ribeirão Preto, SP, Brazil, October 23-27, 2006. IEEE Computer Society 2006, ISBN 0-7695-2680-2 [contents] - 2005
- [j6]Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir, Wilson Rosa de Oliveira:
Equivalence between RAM-based neural networks and probabilistic automata. IEEE Trans. Neural Networks 16(4): 996-999 (2005) - [c12]Shirlly C. M. Silva, Daniel S. A. de Araujo, Raul Benites Paradeda, Valmar S. Severiano-Sobrinho, Marcílio Carlos Pereira de Souto:
Individual Clustering and Homogeneous Cluster Ensemble Approaches Applied to Gene Expression Data. Australian Conference on Artificial Intelligence 2005: 930-933 - [c11]Teresa Bernarda Ludermir, C. R. S. Lopes, A. B. Ludermir, Marcílio Carlos Pereira de Souto:
Neural Network Use for the Identification of Factors Related to Common Mental Disorders. ICANN (1) 2005: 653-658 - [c10]Katti Faceli, André Carlos Ponce de Leon Ferreira de Carvalho, Marcílio Carlos Pereira de Souto:
Evaluation of the Contents of Partitions Obtained with Clustering Gene Expression Data. BSB 2005: 65-76 - [c9]Meika I. Monteiro, Marcílio Carlos Pereira de Souto, Luiz M. G. Gonçalves, Lucymara F. Agnez-Lima:
Machine Learning Techniques for Predicting Bacillus subtilis Promoters. BSB 2005: 77-84 - 2003
- [j5]Teresa Bernarda Ludermir, Marcílio Carlos Pereira de Souto:
Introduction by Guest Editors. Int. J. Neural Syst. 13(2): 55-57 (2003) - 2002
- [j4]Teresa Bernarda Ludermir, Marcílio Carlos Pereira de Souto:
The VIIth Brazilian Symposium on Neural Networks (SBRN'02). J. Intell. Fuzzy Syst. 13(2-4): 61-62 (2002) - [j3]Wilson Rosa de Oliveira, Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir:
Turing's analysis of computation and artificial neural networks. J. Intell. Fuzzy Syst. 13(2-4): 85-98 (2002) - [j2]Ivan G. Costa, Francisco de A. T. de Carvalho, Marcílio Carlos Pereira de Souto:
Comparative study on proximity indices for cluster analysis of gene expression time series. J. Intell. Fuzzy Syst. 13(2-4): 133-142 (2002) - [c8]Ivan G. Costa, Francisco de A. T. de Carvalho, Marcílio Carlos Pereira de Souto:
A Symbolic Approach to Gene Expression Time Series Analysis. SBRN 2002: 25-30 - [c7]Wilson Rosa de Oliveira, Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir:
Turing Machines with Finite Memory. SBRN 2002: 67-73 - [c6]C. R. S. Lopes, Teresa Bernarda Ludermir, Marcílio Carlos Pereira de Souto, A. B. Ludermir:
Neural Networks for the analysis of Common Mental Disorders Factors. SBRN 2002: 114 - [c5]Akio Yamazaki, Teresa Bernarda Ludermir, Marcílio Carlos Pereira de Souto:
Global Optimization Methods for Designing and Training Neural Networks. SBRN 2002: 136-141 - [c4]José Carlos Martins Oliveira, Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir:
Implementation of Probabilistic Automata in Weightless Neural Networks. SBRN 2002: 235 - [c3]Ivan G. Costa, Francisco de A. T. de Carvalho, Marcílio Carlos Pereira de Souto:
Stability Evaluation of Clustering Algorithms for Time Series Gene Expression Data. WOB 2002: 88-90 - [e1]Teresa Bernarda Ludermir, Marcílio Carlos Pereira de Souto:
7th Brazilian Symposium on Neural Networks (SBRN 2002), 11-14 November 2002, Recife, Brazil. IEEE Computer Society 2002, ISBN 0-7695-1709-9 [contents] - 2000
- [c2]Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir, Marcília A. Campos:
Encoding of Probabilistic Automata into RAM-Based Neural Networks. IJCNN (3) 2000: 439-444
1990 – 1999
- 1999
- [b1]Marcílio Carlos Pereira de Souto:
Computability and learnability in sequential weightless neural networks. Imperial College London, UK, 1999 - [j1]Marcílio Carlos Pereira de Souto, Paulo J. L. Adeodato, Teresa Bernarda Ludermir:
Sequential RAM-based Neural Networks: Learnability, Generalisation, Knowledge Extraction, and Grammatical Inference. Int. J. Neural Syst. 9(3): 203-210 (1999) - 1998
- [c1]Marcílio Carlos Pereira de Souto, Paulo J. L. Adeodato:
Learnability in Sequential RAM-based Neural Networks. SBRN 1998: 20-25
Coauthor Index
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
Ivan G. Costa
aka: Ivan Gesteira Costa
aka: Ivan Gesteira Costa
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