Pattern Recognition of Lower Member Skin Ulcers in Medical Images with Machine Learning Algorithms. - Jose Luis Seixas; Sylvio Barbon; Rafael Gomes Mantovani (CBMS, 2015)

To tune or not to tune: Recommending when to adjust SVM hyper-parameters via meta-learning. - Rafael Gomes Mantovani; André Luis Debiaso Rossi; Joaquin Vanschoren; Bernd Bischl; André C. P. L. F. de Carvalho (IJCNN, 2015)

Effectiveness of Random Search in SVM hyper-parameter tuning. - Rafael Gomes Mantovani; André Luis Debiaso Rossi; Joaquin Vanschoren; Bernd Bischl; André C. P. L. F. de Carvalho (IJCNN, 2015)

Meta-learning Recommendation of Default Hyper-parameter Values for SVMs in Classification Tasks. - Rafael Gomes Mantovani; André L. D. Rossi; Joaquin Vanschoren; André C. P. L. F. de Carvalho (MetaSel@PKDD/ECML, 2015)

Hyper-Parameter Tuning of a Decision Tree Induction Algorithm. - Rafael Gomes Mantovani; Tomás Horváth; Ricardo Cerri; Joaquin Vanschoren; André C. P. L. F. de Carvalho (BRACIS, 2016)

Effects of Random Sampling on SVM Hyper-parameter Tuning. - Tomás Horváth; Rafael Gomes Mantovani; André C. P. L. F. de Carvalho (ISDA, 2016)

A Meta-Learning Approach for Recommendation of Image Segmentation Algorithms. - Gabriel F. C. Campos; Sylvio Barbon; Rafael Gomes Mantovani (SIBGRAPI, 2016)

Storage time prediction of pork by Computational Intelligence. - Ana Paula A. C. Barbon; Sylvio Barbon Junior; Rafael Gomes Mantovani; Estefânia Mayumi Fuzyi; Louise Manha Peres; Ana Maria Bridi (Comput. Electron. Agric., 2016)

Incorporating instance correlations in multi-label classification via label-space. - Iuri Bonna M. de Abreu; Rafael Gomes Mantovani; Ricardo Cerri (IJCNN, 2017)

OpenML Benchmarking Suites and the OpenML100. - Bernd Bischl; Giuseppe Casalicchio; Matthias Feurer; Frank Hutter; Michel Lang; Rafael Gomes Mantovani; Jan N. van Rijn; Joaquin Vanschoren (CoRR, 2017)

Dimensionality Reduction for the Algorithm Recommendation Problem. - Edesio Alcobaça; Rafael Gomes Mantovani; André L. D. Rossi; André C. P. L. F. de Carvalho (BRACIS, 2018)

Multi-label Feature Selection Techniques for Hierarchical Multi-label Protein Function Prediction. - Ricardo Cerri; Rafael Gomes Mantovani; Márcio P. Basgalupp; André C. P. L. F. de Carvalho (IJCNN, 2018)

An empirical study on hyperparameter tuning of decision trees. - Rafael Gomes Mantovani; Tomás Horváth; Ricardo Cerri; Sylvio Barbon Junior; Joaquin Vanschoren; André Carlos Ponce de Leon Ferreira de Carvalho (CoRR, 2018)

Applying multi-label techniques in emotion identification of short texts. - Alex Marino Gonçalves de Almeida; Ricardo Cerri; Emerson Cabrera Paraiso; Rafael Gomes Mantovani; Sylvio Barbon Junior (Neurocomputing, 2018)

Towards Meta-Learning for Multi-Target Regression Problems. - Gabriel Jonas Aguiar; Everton José Santana; Saulo Martiello Mastelini; Rafael Gomes Mantovani; Sylvio Barbon Jr. (BRACIS, 2019)

Transfer Learning for Algorithm Recommendation. - Gean Trindade Pereira; Moisés Rocha dos Santos; Edesio Alcobaça; Rafael Gomes Mantovani; André C. P. L. F. de Carvalho (CoRR, 2019)

Machine learning hyperparameter selection for Contrast Limited Adaptive Histogram Equalization. - Gabriel Fillipe Centini Campos; Saulo Martiello Mastelini; Gabriel Jonas Aguiar; Rafael Gomes Mantovani; Leonimer Flavio de Melo; Sylvio Barbon Junior (EURASIP J. Image Video Process., 2019)

A meta-learning recommender system for hyperparameter tuning: Predicting when tuning improves SVM classifiers. - Rafael Gomes Mantovani; André L. D. Rossi; Edesio Alcobaça; Joaquin Vanschoren; André C. P. L. F. de Carvalho (Inf. Sci., 2019)

A meta-learning approach for selecting image segmentation algorithm. - Gabriel Jonas Aguiar; Rafael Gomes Mantovani; Saulo Martiello Mastelini; André C. P. L. F. de Carvalho; Gabriel F. C. Campos; Sylvio Barbon Junior (Pattern Recognit. Lett., 2019)

Rethinking Default Values: a Low Cost and Efficient Strategy to Define Hyperparameters. - Rafael Gomes Mantovani; André Luis Debiaso Rossi; Edesio Alcobaça; Jadson Castro Gertrudes; Sylvio Barbon Junior; André Carlos Ponce de Leon Ferreira de Carvalho (CoRR, 2020)

An Extensive Experimental Evaluation of Automated Machine Learning Methods for Recommending Classification Algorithms (Extended Version). - Márcio P. Basgalupp; Rodrigo C. Barros; Alex Guimarães Cardoso de Sá; Gisele L. Pappa; Rafael Gomes Mantovani; André C. P. L. F. de Carvalho; Alex Alves Freitas (CoRR, 2020)

Learning Abstract Task Representations. - Mikhail M. Meskhi; Adriano Rivolli; Rafael G. Mantovani; Ricardo Vilalta (MetaDL@AAAI, 2021)

Feature Analysis to League of Legends Victory Prediction on the Picks and Bans Phase. - Lincoln Magalhães Costa; Rafael Gomes Mantovani; Francisco Carlos Monteiro Souza; Geraldo Xexéo (CoG, 2021)

Time-Series in Hyper-parameter Initialization of Machine Learning Techniques. - Tomás Horváth; Rafael Gomes Mantovani; André C. P. L. F. de Carvalho (IDEAL, 2021)

Exploring Autoencoders for Feature Extraction in Multi-Target Classification. - Brendon Gouveia Cambuí; Rafael Gomes Mantovani; Ricardo Cerri (IJCNN, 2021)

OpenML Benchmarking Suites. - Bernd Bischl; Giuseppe Casalicchio; Matthias Feurer; Pieter Gijsbers; Frank Hutter; Michel Lang; Rafael Gomes Mantovani; Jan N. van Rijn; Joaquin Vanschoren (NeurIPS Datasets and Benchmarks, 2021)

DP-Symptom-Identifier: uma estratégia para classificar sintomas de depressão utilizando um conjunto de dados textuais na língua portuguesa. - Vinicius Casani; Alinne Cristinne Corrêa Souza; Rafael G. Mantovani; Francisco Carlos M. Souza (STIL, 2021)

An extensive experimental evaluation of automated machine learning methods for recommending classification algorithms. - Márcio P. Basgalupp; Rodrigo C. Barros; Alex Guimarães Cardoso de Sá; Gisele L. Pappa; Rafael Gomes Mantovani; André C. P. L. F. de Carvalho; Alex Alves Freitas (Evol. Intell., 2021)

AutoMMLC: An Automated and Multi-objective Method for Multi-label Classification. - Aline Marques Del Valle; Rafael Gomes Mantovani; Ricardo Cerri (BRACIS (2), 2023)

Hyper-parameter initialization of classification algorithms using dynamic time warping: A perspective on PCA meta-features. - Tomás Horváth; Rafael G. Mantovani; André C. P. L. F. de Carvalho (Appl. Soft Comput., 2023)

A systematic literature review on AutoML for multi-target learning tasks. - Aline Marques Del Valle; Rafael Gomes Mantovani; Ricardo Cerri (Artif. Intell. Rev., 2023)

Classification of the growth level of fungal colonies in solid medium: a machine learning approach. - Edgar de Souza Vismara; Lilian de Souza Vismara; Jose Luis Seixas; Francisco Carlos Monteiro Souza; Rafael Gomes Mantovani (Expert Syst. Appl., 2023)

Design and Evaluation of a Procedurally Generated Dungeon Game. - Arthur R. Pinheiro So; Alinne Cristinne Corrêa Souza; Lincoln Magalhães Costa; Rafael G. Mantovani; Francisco Carlos M. Souza (SBGames, 2024)

An Exploratory Analysis on Gender-Related Dropout Students in Distance Learning Higher Education using Machine Learning. - Gilmar Santos; Alinne Souza; Rafael G. Mantovani; Robinson Crusoé Da Cruz; Thiago Damasceno Cordeiro; Francisco Carlos M. Souza (SBSI, 2024)

Better trees: an empirical study on hyperparameter tuning of classification decision tree induction algorithms. - Rafael Gomes Mantovani; Tomás Horváth; André L. D. Rossi; Ricardo Cerri; Sylvio Barbon Junior; Joaquin Vanschoren; André C. P. L. F. de Carvalho (Data Min. Knowl. Discov., 2024)

Novel applications of item response theory for analysing data set complexity and benchmark selection. - João Luiz Junho Pereira; Alfredo Antonio Alencar Exposito de Queiroz; Telmo de Menezes e Silva Filho; Ana Carolina Lorena; Rafael Gomes Mantovani; Gisele Lobo Pappa; Ricardo Bastos Cavalcante Prudêncio (Mach. Learn., 2025)