Rafael Gomes Mantovani

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André Carlos Ponce de Leon Ferreira...Artificial Intelligence Professor, University of São PauloDirección de correo verificada de icmc.usp.br
Sylvio Barbon JuniorUniversity of Trieste, Department of Engineering and ArchitectureDirección de correo verificada de dia.units.it
Joaquin VanschorenEindhoven University of TechnologyDirección de correo verificada de tue.nl
Ricardo CerriAssistant Professor, Institute of Mathematics and Computer Science, University of São PauloDirección de correo verificada de icmc.usp.br
Andre Luis Debiaso RossiUniversidade Estadual Paulista (UNESP)Dirección de correo verificada de unesp.br
Bernd BischlChair of Statistical Learning and Data Science, LMU MunichDirección de correo verificada de stat.uni-muenchen.de
Tomas HorvathEdinburgh Napier UniversityDirección de correo verificada de napier.ac.uk
Edesio AlcobaçaPhD candidate, Universidade de São PauloDirección de correo verificada de usp.br
Saulo Martiello MasteliniPh.D., Universidade de São PauloDirección de correo verificada de alumni.usp.br
Giuseppe CasalicchioSenior Lecturer and Researcher, LMU Munich, Munich Center for Machine LearningDirección de correo verificada de campus.lmu.de
Gabriel F. C. CamposComputer Science, State University of LondrinaDirección de correo verificada de uel.br
Gabriel Jonas AguiarPh.D. Candidate at Virginia Commonwealth UniversityDirección de correo verificada de vcu.edu
Michel LangTU Dortmund; LMU MunichDirección de correo verificada de statistik.tu-dortmund.de
Jan N. van RijnLeiden UniversityDirección de correo verificada de liacs.leidenuniv.nl
Frank HutterELLIS Institute Tübingen & Professor, University of Freiburg, GermanyDirección de correo verificada de cs.uni-freiburg.de
Matthias FeurerLMU MunichDirección de correo verificada de stat.uni-muenchen.de
Francisco Carlos M. SouzaUniversidade Tecnológica Federal do ParanáDirección de correo verificada de icmc.usp.br
José Luis Seixas JuniorPhD student, Eötvös Loránd UniversityDirección de correo verificada de inf.elte.hu
Douglas Fernandes BarbinUniversity of CampinasDirección de correo verificada de unicamp.br
Leonimer Flávio de MeloProfessor Dr. de Engenharia Elétrica, Universidade Estadual de LondrinaDirección de correo verificada de uel.br

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Rafael Gomes Mantovani

Federal Technology University - Paraná, campus of Apucarana

Dirección de correo verificada de utfpr.edu.br

Machine Learning Hyperparameter optimization Meta-learning Recommending Systems


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Effectiveness of random search in SVM hyper-parameter tuning RG Mantovani, ALD Rossi, J Vanschoren, B Bischl, AC De Carvalho 2015 international joint conference on neural networks (IJCNN), 1-8, 2015	188	2015
Openml benchmarking suites B Bischl, G Casalicchio, M Feurer, P Gijsbers, F Hutter, M Lang, ... arXiv preprint arXiv:1708.03731, 2017	155	2017
Hyper-parameter tuning of a decision tree induction algorithm RG Mantovani, T Horváth, R Cerri, J Vanschoren, AC De Carvalho 2016 5th Brazilian Conference on Intelligent Systems (BRACIS), 37-42, 2016	146	2016
Machine learning hyperparameter selection for contrast limited adaptive histogram equalization GFC Campos, SM Mastelini, GJ Aguiar, RG Mantovani, LF Melo, ... EURASIP Journal on Image and Video Processing 2019, 1-18, 2019	119	2019
A meta-learning recommender system for hyperparameter tuning: Predicting when tuning improves SVM classifiers RG Mantovani, ... Information Sciences 501, 193-221, 2019	103*	2019
Better trees: an empirical study on hyperparameter tuning of classification decision tree induction algorithms R Gomes Mantovani, T Horvath, ALD Rossi, R Cerri, S Barbon Junior, ... Data Mining and Knowledge Discovery 38, 1364-1416, 2024	94*	2024
To tune or not to tune: recommending when to adjust SVM hyper-parameters via meta-learning RG Mantovani, ALD Rossi, J Vanschoren, B Bischl, AC Carvalho 2015 International joint conference on neural networks (IJCNN), 1-8, 2015	92	2015
OpenML benchmarking suites and the OpenML100 B Bischl, G Casalicchio, M Feurer, F Hutter, M Lang, RG Mantovani, ... stat 1050, 11, 2017	86	2017
Applying multi-label techniques in emotion identification of short texts AMG Almeida, R Cerri, EC Paraiso, RG Mantovani, SB Junior Neurocomputing 320, 35-46, 2018	64	2018
Machine learning applied to near‐infrared spectra for chicken meat classification S Barbon Jr, APA Costa Barbon, RG Mantovani, DF Barbin Journal of Spectroscopy 2018 (1), 8949741, 2018	49	2018
A meta-learning approach for selecting image segmentation algorithm GJ Aguiar, RG Mantovani, SM Mastelini, AC de Carvalho, GFC Campos, ... Pattern Recognition Letters 128, 480-487, 2019	47	2019
Storage time prediction of pork by Computational Intelligence APAC Barbon, S Barbon Jr, RG Mantovani, EM Fuzyi, LM Peres, AM Bridi Computers and Electronics in Agriculture 127, 368-375, 2016	46	2016
Pattern recognition of lower member skin ulcers in medical images with machine learning algorithms JL Seixas, S Barbon, RG Mantovani 2015 IEEE 28th International Symposium on Computer-Based Medical Systems, 50-53, 2015	24	2015
Meta-learning Recommendation of Default Hyper-parameter Values for SVMs in Classification Tasks. RG Mantovani, ALD Rossi, J Vanschoren, AC de Carvalho MetaSel@ PKDD/ECML, 80-92, 2015	23	2015
A meta-learning approach for recommendation of image segmentation algorithms GFC Campos, S Barbon, RG Mantovani 2016 29th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI …, 2016	22	2016
Effects of random sampling on svm hyper-parameter tuning T Horváth, RG Mantovani, AC de Carvalho International Conference on Intelligent Systems Design and Applications, 268-278, 2016	18	2016
Multi-label feature selection techniques for hierarchical multi-label protein function prediction R Cerri, RG Mantovani, MP Basgalupp, AC de Carvalho 2018 International Joint Conference on Neural Networks (IJCNN), 1-7, 2018	17	2018
Feature analysis to league of legends victory prediction on the picks and bans phase LM Costa, RG Mantovani, FCM Souza, G Xexeo 2021 IEEE Conference on Games (CoG), 01-05, 2021	16	2021
Learning abstract task representations MM Meskhi, A Rivolli, RG Mantovani, R Vilalta AAAI Workshop on Meta-Learning and MetaDL Challenge, 127-137, 2021	11	2021
Rethinking default values: A low cost and efficient strategy to define hyperparameters RG Mantovani, ALD Rossi, E Alcobaça, JC Gertrudes, SB Junior, ... arXiv preprint arXiv:2008.00025, 2020	11	2020

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