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Ministério da Defesa (Brasil). Instituto Tecnológico de Aeronáutica (ITA). Divisão de Ciência da Computação (IEC) (Institutional affiliation for the last research proposal) Birthplace: Brazil
Graduate at Computer Science from Universidade de São Paulo (2001) and PhD at Computer Science from Universidade de São Paulo - São Carlos (2006). Professor at Instituto Tecnológico de Aeronáutica (ITA). Has experience in Computer Science, focusing on Artificial Intelligence, acting on the following subjects: supervised Machine Learning, Data Mining, Data Science. (Source: Lattes Curriculum)
Machine Learning (ML) techniques have been successfully employed in the solution of various data classification problems. Recently some studies are devoted to understand how quantitative measures quantifying the complexity of data sets used for classification, such as the geometric overlap between classes, affects the performance of ML techniques. Among the contributions of this approach …
Various space agencies are interested in monitoring the passage of meteors in Earth's atmosphere, such as NASA, that developed the CAMS project (Cameras for Allsky Meteor Surveillance). In Brazil, the EXOSS (Exploring the Southern Sky) organization uses citizen science to monitor the night sky, relying on low budget stations that are mounted by professional and amateur astronomers across …
Many practical problems involve distinguishing data from multiple classes. One possible approach to deal with such multiclass classification problems is to decompose them into several binary sub-problems and combine their solutions. The One-versus-One decomposition, which generates a binary subproblem for each pair of classes is one of the most widely used decomposition strategies. Standa…
In the current era, with the emergence of the so-called digital identity, identity theft has gained new momentum. In view of this scenario, new user authentication mechanisms were developed. However, these processes are generally applied only in the system startup. Consequently, the system would be vulnerable in case the user leaves the workstation and do not end the session.With the aim …
(Only some records are available in English at this moment)
The areas of Meta-learning (MtL) and Automatic Machine Learning (AutoML) have emerged in the last years with successful solutions to ease the usage of Machine Learning (ML) techniques by interested end-users with low expertise in ML. Usually the MtL and AutoML solutions leverage on knowledge from problems for which the solutions are known, gathered in public repositories. One popular repo…
| 5 / 3 | Completed research grants |
| 6 / 4 | Completed scholarships in Brazil |
| 1 / 1 | Ongoing scholarships abroad |
| 12 / 8 | All research grants and scholarships |
| Associated processes | |
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
| Publications | 12 |
| Citations | 25 |
| Cit./Article | 2.1 |
| Data from Web of Science | |
GARCIA, LUIS P. F.; LEHMANN, JENS; DE CARVALHO, ANDRE C. P. L. F.; LORENA, ANA C.. New label noise injection methods for the evaluation of noise filters. KNOWLEDGE-BASED SYSTEMS, v. 163, p. 693-704, JAN 1 2019. Web of Science Citations: 0. (16/18615-0, 13/07375-0, 12/22608-8)
PISANI, PAULO HENRIQUE; POH, NORMAN; DE CARVALHO, ANDRE C. P. L. F.; LORENA, ANA CAROLINA. Score normalization applied to adaptive biometric systems. COMPUTERS & SECURITY, v. 70, p. 565-580, SEP 2017. Web of Science Citations: 2. (12/25032-0, 13/07375-0, 12/22608-8)
LORENA, ANA C.; MACIEL, ARON I.; DE MIRANDA, PERICLES B. C.; COSTA, IVAN G.; PRUDENCIO, RICARDO B. C.. Data complexity meta-features for regression problems. MACHINE LEARNING, v. 107, n. 1, SI, p. 209-246, JAN 2018. Web of Science Citations: 5. (12/22608-8)
MORALES, PABLO; LUENGO, JULIAN; GARCIA, LUIS P. F.; LORENA, ANA C.; DE CARVALHO, ANDRE C. P. L. F.; HERRERA, FRANCISCO. The NoiseFiltersR Package: Label Noise Preprocessing in R. R JOURNAL, v. 9, n. 1, p. 219-228, JUN 2017. Web of Science Citations: 3. (13/07375-0, 12/22608-8, 11/14602-7)
PISANI, PAULO HENRIQUE; LORENA, ANA CAROLINA; DE CARVALHO, ANDRE C. P. L. F.. Adaptive algorithms applied to accelerometer biometrics in a data stream context. Intelligent Data Analysis, v. 21, n. 2, p. 353-370, 2017. Web of Science Citations: 3. (12/25032-0, 13/07375-0, 12/22608-8)
TRAMBAIOLLI, L. R.; SPOLAOR, N.; LORENA, A. C.; ANGHINAH, R.; SATO, J. R.. Feature selection before EEG classification supports the diagnosis of Alzheimer's disease. CLINICAL NEUROPHYSIOLOGY, v. 128, n. 10, p. 2058-2067, OCT 2017. Web of Science Citations: 10. (13/10952-9, 12/22608-8, 13/10498-6, 13/00506-1)
LORENA, ANA C.; CARVALHO, ANDRÉ C. P. L. F. DE. Evaluation of noise reduction techniques in the splice junction recognition problem. GENETICS AND MOLECULAR BIOLOGY, v. 27, n. 4, p. 665-672, Dec. 2004.
BARELLA, VICTOR H.; GARCIA, LUIS P. F.; DE SOUTO, MARCILIO C. P.; LORENA, ANA C.; DE CARVALHO, ANDRE C. P. L. F.. Assessing the data complexity of imbalanced datasets. INFORMATION SCIENCES, v. 553, p. 83-109, APR 2021. Web of Science Citations: 0. (13/07375-0, 15/01382-0, 12/22608-8)
QUITERIO, THAISE M.; LORENA, ANA C.. Using complexity measures to determine the structure of directed acyclic graphs in multiclass classification. APPLIED SOFT COMPUTING, v. 65, p. 428-442, APR 2018. Web of Science Citations: 1. (12/22608-8, 15/17291-3)
SPOLAOR, NEWTON; LORENA, ANA CAROLINA; LEE, HUEI DIANA. Feature Selection via Pareto Multi-objective Genetic Algorithms. APPLIED ARTIFICIAL INTELLIGENCE, v. 31, n. 9-10, p. 764-791, 2017. Web of Science Citations: 0. (09/12963-2, 12/22608-8)
PISANI, PAULO HENRIQUE; LORENA, ANA CAROLINA; DE CARVALHO, ANDRE C. P. L. F.. Adaptive Biometric Systems Using Ensembles. IEEE INTELLIGENT SYSTEMS, v. 33, n. 2, p. 19-28, MAR-APR 2018. Web of Science Citations: 1. (12/25032-0, 13/07375-0, 12/22608-8)
PIMENTEL, BRUNO ALMEIDA; DE CARVALHO, ANDRE C. P. L. F.. A Meta-learning approach for recommending the number of clusters for clustering algorithms. KNOWLEDGE-BASED SYSTEMS, v. 195, MAY 11 2020. Web of Science Citations: 0. (16/18615-0, 17/20265-0, 12/22608-8)
RIVOLLI, ADRIANO; READ, JESSE; SOARES, CARLOS; PFAHRINGER, BERNHARD; DE CARVALHO, ANDRE C. P. L. F.. An empirical analysis of binary transformation strategies and base algorithms for multi-label learning. MACHINE LEARNING, v. 109, n. 8, JUN 2020. Web of Science Citations: 0. (16/18615-0, 13/07375-0, 12/22608-8)
(References retrieved automatically from State of São Paulo Research Institutions)
LORENA, Ana Carolina. "Investigação de estratégias para a geração de máquinas de vetores de suporte multiclasses". Tese (Doutorado) - Instituto de Ciências Matemáticas e de Computação. Universidade de São Paulo (USP). São Carlos. (02/00969-7)