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361 results on '"Ferreira, O"'

7. A generalized conditional gradient method for multiobjective composite optimization problems.

Author

Assunção, P. B., Ferreira, O. P., and Prudente, L. F.

Subjects
*MULTI-objective optimization, *SMOOTHNESS of functions
Abstract

This article deals with multiobjective composite optimization problems that consist of simultaneously minimizing several objective functions, each of which is composed of a combination of smooth and non-smooth functions. To tackle these problems, we propose a generalized version of the conditional gradient method, also known as Frank-Wolfe method. The method is analysed with three step size strategies, including Armijo-type, adaptive, and diminishing step sizes. We establish asymptotic convergence properties and iteration-complexity bounds, with and without convexity assumptions on the objective functions. Numerical experiments illustrating the practical behaviour of the methods are presented. [ABSTRACT FROM AUTHOR]

Published
2025
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24. Reducing the projection onto the monotone extended second-order cone to the pool-adjacent-violators algorithm of isotonic regression.

Author

Ferreira, O. P., Gao, Y., and Németh, S. Z.

Subjects
*ISOTONIC regression, *METRIC projections, *ALGORITHMS
Abstract

This paper introduces the monotone extended second-order cone (MESOC), which is related to the monotone cone and the second-order cone. Some properties of the MESOC are presented and its dual cone is computed. Projecting onto the MESOC is reduced to the pool-adjacent-violators algorithm (PAVA) of isotonic regression. An application of MESOC to portfolio optimization is provided. Some broad descriptions of possible MESOC-regression models are also outlined. [ABSTRACT FROM AUTHOR]

Published
2024
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31. A generalized conditional gradient method for multiobjective composite optimization problems

Author

Assunção, P. B., Ferreira, O. P., and Prudente, L. F.

Subjects
Optimization and Control (math.OC), FOS: Mathematics, Mathematics - Optimization and Control
Abstract

This article deals with multiobjective composite optimization problems that consist of simultaneously minimizing several objective functions, each of which is composed of a combination of smooth and non-smooth functions. To tackle these problems, we propose a generalized version of the conditional gradient method, also known as Frank-Wolfe method. The method is analyzed with three step size strategies, including Armijo-type, adaptive, and diminishing step sizes. We establish asymptotic convergence properties and iteration-complexity bounds, with and without convexity assumptions on the objective functions. Numerical experiments illustrating the practical behavior of the methods are presented.

Published
2023

38. AMAZONIA CAMTRAP: a dataset of mammal, bird, and reptile species recorded with camera traps in the Amazon forest

Author

Antunes, A., Montanarin, A., Gräbin, D., dos Santos Monteiro, E., Ferreira de Pinho, F., Alvarenga, G., Ahumada, J., Wallace, R., Ramalho, E., Barnett, A., Bager, A., Lopes, C., Martins, A., Keuroghlian, A., Giroux, A., Herrera, A., de Correa, A., Paula, A., Meiga, A., de Almeida Jácomo, A., de Barros Barban, A., de Almeida Coelho, A., Camilo, A., Nunes, A., dos Santos Maroclo Gomes, A., da Zanzini, S., Carlos, A., Castro, A., Desbiez, A., Figueiredo, A., de Thoisy, B., Gauzens, B., Oliveira, B., de Lima, A., Peres, C., Durigan, C., Brocardo, C., da Rosa, A., Zárate-Castañeda, C., Monteza-Moreno, C., Carnicer, C., Trinca, C., Polli, D., Ferraz da Silva , D., Lane, D., Gomes da Rocha, D., Barcelos, D., Auz, D., Rosa, D., Silva, D., Silvério, D., Eaton, D., Nakano-Oliveira, E., Venticinque, E., Carvalho Junior, E., Mendonça, E., Vieira, E., Isasi-Catalá, E., Fischer, E., Castro, E., Oliveira, E., de Melo, F., de Lima Muniz, F., Rohe, F., Baccaro, F., Michalski, F., Paim, F., Santos, F., Anaguano, F., Palmeira, F., Reis, F., Aguiar-Silva, F., de Avila Batista, G., Zapata-Ríos, G., Forero-Medina, G., De Souza Ferreira Neto, G., Alves, G., Ayala, G., Pedersoli, G., El Bizri, H., Alves do Prado, H., Mozerle, H., Costa, H., Lima, I., Palacios, J., de Resende Assis, J., Boubli, J., Metzger, J., Teixeira, J., Miranda, J., Polisar, J., Salvador, J., Borges-Almeida, K., Didier, K., Dayane de Lima Pereira, K., Torralvo, K., Gajapersad, K., Silveira, L., Maioli, L., Maracahipes-Santos, L., Valenzuela, L., Benavalli, L., Fletcher, L., Paolucci, L., Zanzini, L., Zago da Silva, L., Rodrigues, R., Cláudio, L., Benchimol, M., Oliveira, M., Lima, M., Basto da Silva, M., Junior, d., Augusto, M., Viscarra, M., Cohn-Haft, M., Abrahams, M., Benedetti, M., Marmontel, M., Hirt, M., Tôrres, N., Junior, C., Ferreira, O., Alvarez-Loayza, P., Jansen, P., Prist, P., Brando, P., Bernardes Perônico, P., do Nascimento Leite, R., Rabelo, R., Sollmann, R., Beltrão-Mendes, R., Ferreira, R., Coutinho, R., Oliveira, R., Ilha, R., Hilário, R., Pires, R., Sampaio, R., da Silva Moreira, R., Botero-Arias, R., Vasquez Martinez, R., de Albuquerque Nóbrega, R., Fadini, R., Morato, R., Carneiro, R., Almeida, R., Ramos, R., Schaub, R., Dornas, R., Cueva, R., Rolim, S., Laurindo, S., Espinosa, S., Fernandes, T., Sanaiotti, T., Gomide Alvim, T., Dornas, T., Piña, T., Caetano Andrade, V., Santiago, W., Magnusson, W., Campos, Z., and Ribeiro, M.

Abstract

The Amazon forest has the highest biodiversity on earth. However, information on Amazonian vertebrate diversity is still deficient and scattered across the published, peer-reviewed and grey literature and in unpublished raw data. Camera traps are an effective non-invasive method of surveying vertebrates, applicable to different scales of time and space. In this study, we organized and standardized camera trap records from different Amazon regions to compile the most extensive dataset of inventories of mammal, bird and reptile species ever assembled for the area. The complete dataset comprises 154,123 records of 317 species (185 birds, 119 mammals and 13 reptiles) gathered from surveys from the Amazonian portion of eight countries (Brazil, Bolivia, Colombia, Ecuador, French Guiana, Peru, Suriname and Venezuela). The most frequently recorded species per taxa were: mammals

Published
2022

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