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Journal Articles
- 2020
[j3]Madson L. D. Dias, Átilla N. Maia, Ajalmar R. da Rocha Neto, João P. P. Gomes:
Parsimonious Minimal Learning Machine via Multiresponse Sparse Regression. Int. J. Neural Syst. 30(5): 2050023:1-2050023:17 (2020)- 2018
- [j2]Madson Luiz Dantas Dias, Lucas Silva de Sousa, Ajalmar R. da Rocha Neto
, Ananda L. Freire:
Fixed-Size Extreme Learning Machines Through Simulated Annealing. Neural Process. Lett. 48(1): 135-151 (2018) - 2017
- [j1]Madson Luiz Dantas Dias, Ajalmar R. da Rocha Neto:
Training soft margin support vector machines by simulated annealing: A dual approach. Expert Syst. Appl. 87: 157-169 (2017)
Conference and Workshop Papers
- 2020
- [c9]Madson L. D. Dias, César Lincoln C. Mattos, Ticiana L. Coelho da Silva, José Antônio Fernandes de Macêdo, Wellington C. P. Silva:
Anomaly Detection in Trajectory Data with Normalizing Flows. IJCNN 2020: 1-8 - 2019
- [c8]Madson Luiz Dantas Dias, Lucas Silva de Sousa, Ajalmar R. da Rocha Neto, César L. C. Mattos, João P. P. Gomes, Tommi Kärkkäinen:
Sparse minimal learning machine using a diversity measure minimization. ESANN 2019 - 2018
- [c7]Madson Luiz Dantas Dias, Ananda L. Freire, Amauri H. Souza Júnior, Ajalmar R. da Rocha Neto, João Paulo Pordeus Gomes:
Sparse Minimal Learning Machines Via L_1/2 Norm Regularization. BRACIS 2018: 206-211 - [c6]Madson Luiz Dantas Dias, Lucas Silva de Sousa, Ajalmar R. da Rocha Neto, Amauri H. Souza Júnior:
Opposite neighborhood: a new method to select reference points of minimal learning machines. ESANN 2018 - [c5]Átilla N. Maia, Madson Luiz Dantas Dias, João P. P. Gomes, Ajalmar R. da Rocha Neto:
Optimally Selected Minimal Learning Machine. IDEAL (1) 2018: 670-678 - [c4]José A. V. Florêncio, Madson Luiz Dantas Dias, Ajalmar R. da Rocha Neto, Amauri Holanda de Souza Júnior:
A Fuzzy C-means-based Approach for Selecting Reference Points in Minimal Learning Machines. NAFIPS 2018: 398-407 - 2017
- [c3]Shara S. A. Alves, Madson Luiz Dantas Dias, Ajalmar R. da Rocha Neto, Ananda L. Freire:
Evolutionary Support Vector Regression via Genetic Algorithms: A Dual Approach. IWANN (1) 2017: 85-97 - 2016
- [c2]Madson Luiz Dantas Dias, Ajalmar R. da Rocha Neto:
Evolutionary support vector machines: A dual approach. CEC 2016: 2185-2192 - [c1]Madson Luiz Dantas Dias, Ajalmar R. da Rocha Neto:
A Novel Simulated Annealing-Based Learning Algorithm for Training Support Vector Machines. ISDA 2016: 341-351
Informal and Other Publications
- 2020
- [i1]Madson Luiz Dantas Dias, César Lincoln C. Mattos, Ticiana L. Coelho da Silva, José Antônio Fernandes de Macêdo, Wellington C. P. Silva:
Anomaly Detection in Trajectory Data with Normalizing Flows. CoRR abs/2004.05958 (2020)
Coauthor Index
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