Follow
Andre Luis Debiaso Rossi
Andre Luis Debiaso Rossi
Verified email at unesp.br
Title
Cited by
Cited by
Year
Deep learning for biological image classification
C Affonso, ALD Rossi, FHA Vieira, ACP de Leon Ferreira
Expert systems with applications 85, 114-122, 2017
3292017
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
1802015
Combining meta-learning and search techniques to select parameters for support vector machines
TAF Gomes, RBC Prudêncio, C Soares, ALD Rossi, A Carvalho
Neurocomputing 75 (1), 3-13, 2012
1742012
MetaStream: A meta-learning based method for periodic algorithm selection in time-changing data
ALD Rossi, ACP de Leon Ferreira, C Soares, BF De Souza
Neurocomputing 127, 52-64, 2014
952014
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
882015
A meta-learning recommender system for hyperparameter tuning: Predicting when tuning improves SVM classifiers
RG Mantovani, ALD Rossi, E Alcobaça, J Vanschoren, AC de Carvalho
Information Sciences 501, 193-221, 2019
832019
An empirical study on hyperparameter tuning of decision trees
RG Mantovani, T Horváth, R Cerri, SB Junior, J Vanschoren, ...
arXiv preprint arXiv:1812.02207, 2018
77*2018
N-BEATS-RNN: deep learning for time series forecasting
A Sbrana, ALD Rossi, MC Naldi
2020 19th IEEE International Conference on Machine Learning and Applications …, 2020
252020
Bio-inspired optimization techniques for svm parameter tuning
ALD Rossi, AC de Carvalho
2008 10th Brazilian symposium on neural networks, 57-62, 2008
242008
Edesio Alcobaça, Joaquin Vanschoren, and André CPLF de Carvalho. A meta-learning recommender system for hyperparameter tuning: Predicting when tuning improves SVM classifiers
RG Mantovani, ALD Rossi
Information Sciences 501, 193-221, 2019
222019
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
222015
Combining meta-learning and search techniques to svm parameter selection
TAF Gomes, RBC Prudȇncio, C Soares, ALD Rossi, A Carvalho
2010 Eleventh Brazilian Symposium on Neural Networks, 79-84, 2010
212010
Meta-learning for periodic algorithm selection in time-changing data
ALD Rossi, AC Carvalho, C Soares
2012 Brazilian Symposium on Neural Networks, 7-12, 2012
192012
Predicting execution time of machine learning tasks using metalearning
R Priya, BF de Souza, ALD Rossi, AC de Carvalho
2011 World Congress on Information and Communication Technologies, 1193-1198, 2011
192011
Micro-MetaStream: Algorithm selection for time-changing data
ALD Rossi, C Soares, BF de Souza, ACP de Leon Ferreira
Information Sciences 565, 262-277, 2021
162021
A guidance of data stream characterization for meta-learning
ALD Rossi, BF De Souza, C Soares, A de Leon Ferreira de Carvalho, ...
Intelligent Data Analysis 21 (4), 1015-1035, 2017
162017
Using genetic algorithms to improve prediction of execution times of ML tasks
R Priya, BF de Souza, ALD Rossi, AC de Carvalho
Hybrid Artificial Intelligent Systems: 7th International Conference, HAIS …, 2012
152012
Biological actions, electrical conductance and silicon-containing microparticles of arsenicum album prepared in plastic and glass vials
LC Dalboni, C de Paula Coelho, RRP Pedro, MS Correia, FR de Santana, ...
Homeopathy 108 (01), 012-023, 2019
122019
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
112020
Protein classification using artificial neural networks with different protein encoding methods
ALD Rossi, MA de Oliveira Camargo-Brunetto
Seventh international conference on intelligent systems design and …, 2007
112007
The system can't perform the operation now. Try again later.
Articles 1–20