By Associate Professor Gustavo Batista

Book Chapters

Li F; Gharakheili HH; Batista G, 2024, 'Quantification Over Time', in Lecture Notes in Computer Science, Springer Nature Switzerland, pp. 282 - 299, http://dx.doi.org/10.1007/978-3-031-70362-1_17

da Silva TP; Parmezan ARS; Batista GEAPA, 2022, 'Geographic Context-Based Stacking Learning for Election Prediction from Socio-economic Data', in , pp. 641 - 656, http://dx.doi.org/10.1007/978-3-031-21686-2_44

NADAI BLD; MOURA L; MALETZKE AG; BATISTA GEAPA; CORBI JJ, 2021, 'TECNOLOGIA NO MONITORAMENTO AMBIENTAL DE MOSQUITOS TRANSMISSORES DE DOENÇAS: QUAIS SÃO OS DESAFIOS? UMA BREVE REVISÃO', in INDICADORES BIOLÓGICOS DE QUALIDADE EM AMBIENTES AQUÁTICOS CONTINENTAIS: MÉTRICAS E RECORTES PARA ANÁLISES, RFB Editora, http://dx.doi.org/10.46898/rfb.9786558891321.8

dos Reis D; Maletzke A; Cherman E; Batista G, 2019, 'One-Class Quantification', in Machine Learning and Knowledge Discovery in Databases, Springer Nature, pp. 273 - 289, http://dx.doi.org/10.1007/978-3-030-10925-7_17

Maletzke AG; Lee HD; Enrique G; Batista APA; Coy CSR; Fagundes JAJ; Chung WF, 2014, 'Time series classification with motifs and characteristics', in Soft Computing for Business Intelligence, Springer, Berlin, Heidelberg, pp. 125 - 138

Journal articles

de Nadai BL; Moura L; Castro GB; Silva KJS; Maletzke AG; Corbi JJ; Batista GEAPA; Machado RB, 2024, 'Can microplastic contamination affect the wing morphology and wingbeat frequency of Aedes aegypti (Diptera: Culicidae) mosquitoes?', Environmental Science and Pollution Research, 31, pp. 59289 - 59301, http://dx.doi.org/10.1007/s11356-024-35161-1

Donyavi Z; Serapiao ABS; Batista G, 2024, 'MC-SQ and MC-MQ: Ensembles for Multi-Class Quantification', IEEE Transactions on Knowledge and Data Engineering, 36, pp. 4007 - 4019, http://dx.doi.org/10.1109/TKDE.2024.3372011

Pashamokhtari A; Batista G; Gharakheili HH, 2023, 'Efficient IoT Traffic Inference: From Multi-view Classification to Progressive Monitoring', ACM Transactions on Internet of Things, 5, http://dx.doi.org/10.1145/3625306

Pashamokhtari A; Okui N; Nakahara M; Kubota A; Batista G; Habibi Gharakheili H, 2023, 'Dynamic Inference from IoT Traffic Flows under Concept Drifts in Residential ISP Networks', IEEE Internet of Things Journal, 10, pp. 15761 - 15773, http://dx.doi.org/10.1109/JIOT.2023.3265012

Parmezan ARS; Souza VMA; Seth A; Žliobaitė I; Batista GEAPA, 2022, 'Hierarchical classification of pollinating flying insects under changing environments', Ecological Informatics, 70, http://dx.doi.org/10.1016/j.ecoinf.2022.101751

Tsutsui Da Silva L; Souza VMA; Batista GEAPA, 2022, 'An Open-Source Tool for Classification Models in Resource-Constrained Hardware', IEEE Sensors Journal, 22, pp. 544 - 554, http://dx.doi.org/10.1109/JSEN.2021.3128130

Parmezan ARS; Souza VMA; Batista GEAPA, 2022, 'Time Series Prediction via Similarity Search: Exploring Invariances, Distance Measures and Ensemble Functions', IEEE Access, 10, pp. 78022 - 78043, http://dx.doi.org/10.1109/ACCESS.2022.3192849

de Nadai BL; Maletzke AG; Corbi JJ; Batista GEAPA; Reiskind MH, 2021, 'The impact of body size on Aedes [Stegomyia] aegypti wingbeat frequency: implications for mosquito identification', Medical and Veterinary Entomology, 35, pp. 617 - 624, http://dx.doi.org/10.1111/mve.12540

Li J; Sharma A; Mishra D; Batista G; Seneviratne A, 2021, 'COVID-Safe Spatial Occupancy Monitoring Using OFDM-Based Features and Passive WiFi Samples', ACM Transactions on Management Information Systems, 12, pp. 1 - 24, http://dx.doi.org/10.1145/3472668

Parmezan ARS; Souza VMA; Žliobaitė I; Batista GEAPA, 2021, 'Changes in the wing-beat frequency of bees and wasps depending on environmental conditions: a study with optical sensors', Apidologie, 52, pp. 731 - 748, http://dx.doi.org/10.1007/s13592-021-00860-y

Souza VMA; dos Reis DM; Maletzke AG; Batista GEAPA, 2020, 'Challenges in benchmarking stream learning algorithms with real-world data', Data Mining and Knowledge Discovery, 34, pp. 1805 - 1858, http://dx.doi.org/10.1007/s10618-020-00698-5

Reis DD; de Souto M; de Sousa E; Batista G, 2020, 'Quantifying With Only Positive Training Data', arXiv preprint arXiv:2004.10356

Parmezan ARS; Souza VMA; Batista GEAPA, 2019, 'Evaluation of statistical and machine learning models for time series prediction: Identifying the state-of-the-art and the best conditions for the use of each model', Information Sciences, 484, pp. 302 - 337

Silva DF; Yeh C-CM; Zhu Y; Batista GEAPA; Keogh E, 2019, 'Fast similarity matrix profile for music analysis and exploration', IEEE Transactions on Multimedia, 21, pp. 29 - 38, http://dx.doi.org/10.1109/TMM.2018.2849563

Maletzke AG; dos Reis DM; Batista GEAPA, 2018, 'Combining instance selection and self-training to improve data stream quantification', Journal of the Brazilian Computer Society, 24, pp. 12 - 12, http://dx.doi.org/10.1186/s13173-018-0076-0

Silva DF; Giusti R; Keogh E; Batista GEAPA, 2018, 'Speeding up similarity search under dynamic time warping by pruning unpromising alignments', Data Mining and Knowledge Discovery, 32, pp. 988 - 1016

Souza V; Rossi RG; Batista GEAPA; Rezende SO, 2017, 'Unsupervised active learning techniques for labeling training sets: An experimental evaluation on sequential data', Intelligent Data Analysis, 21, pp. 1061 - 1095

Batista GEAPA; Delgado M; Bernardini F, 2015, 'ENIAC 2013 Special Issue', Journal of Intelligent and Robotic Systems: Theory and Applications, 80, pp. 225 - 226, http://dx.doi.org/10.1007/s10846-015-0260-9

Silva DF; Souza VMA; Ellis DPW; Keogh EJ; Batista GEAPA, 2015, 'Exploring Low Cost Laser Sensors to Identify Flying Insect Species: Evaluation of Machine Learning and Signal Processing Methods', Journal of Intelligent and Robotic Systems: Theory and Applications, 80, pp. 313 - 330, http://dx.doi.org/10.1007/s10846-014-0168-9

Prati RC; Batista GEAPA; Silva DF, 2015, 'Class imbalance revisited: a new experimental setup to assess the performance of treatment methods', Knowledge and Information Systems, 45, pp. 247 - 270

Silva DF; Souza VMA; Ellis DPW; Keogh EJ; Batista GEAPA, 2015, 'Exploring low cost laser sensors to identify flying insect species', Journal of Intelligent & Robotic Systems, 80, pp. 313 - 330

Chen Y; Why A; Batista G; Mafra-Neto A; Keogh E, 2014, 'Flying Insect Classification with Inexpensive Sensors', Journal of Insect Behavior, 27, pp. 657 - 677, http://dx.doi.org/10.1007/s10905-014-9454-4

Batista GEAPA; Keogh EJ; Tataw OM; De Souza VMA, 2014, 'CID: an efficient complexity-invariant distance for time series', Data Mining and Knowledge Discovery, 28, pp. 634 - 669

Del Gaudio R; Batista G; Branco A, 2014, 'Coping with highly imbalanced datasets: A case study with definition extraction in a multilingual setting', Natural Language Engineering, 20, pp. 327 - 359

Chen Y; Why A; Batista G; Mafra-Neto A; Keogh E, 2014, 'Flying insect classification with inexpensive sensors', Journal of insect behavior, 27, pp. 657 - 677

Chen Y; Why A; Batista G; Mafra-Neto A; Keogh E, 2014, 'Flying insect detection and classification with inexpensive sensors', JoVE (Journal of Visualized Experiments), pp. e52111 - e52111

Parmezan ARS; Batista GEAPA; others , 2014, 'ICMC-USP time series prediction repository', Instituto de Ciências Matemáticas e de Computaçao, Universidade de Sao Paulo, Sao Carlos, Brasil. URL https://goo. gl/uzxGZJ

Silva DF; de Souza VMAA; Batista GEAPA, 2013, 'A comparative study between MFCC and LSF coefficients in automatic recognition of isolated digits pronounced in Portuguese and English', Acta Scientiarum. Technology, 35, pp. 621 - 628

Rakthanmanon T; Campana B; Mueen A; Batista G; Westover B; Zhu Q; Zakaria J; Keogh E, 2013, 'Addressing big data time series: Mining trillions of time series subsequences under dynamic time warping', ACM Transactions on Knowledge Discovery from Data (TKDD), 7, pp. 1 - 31

Rakthanmanon T; Campana B; Mueen A; Batista G; Westover B; Zhu Q; Zakaria J; Keogh E, 2013, 'Addressing Big Data Time Series: Mining Trillions of Time Series Subsequences Under Dynamic Time Warping.', ACM Trans Knowl Discov Data, 7, https://www.ncbi.nlm.nih.gov/pubmed/31607834

Prati RC; Batista GEAPA, 2012, 'A complexity-invariant measure based on fractal dimension for time series classification', International Journal of Natural Computing Research (IJNCR), 3, pp. 59 - 73

Prati RC; Batista GEAPA; Monard MC, 2011, 'A survey on graphical methods for classification predictive performance evaluation', IEEE Transactions on Knowledge and Data Engineering, 23, pp. 1601 - 1618, http://dx.doi.org/10.1109/TKDE.2011.59

Milaré CR; Batista GEAPA; Carvalho ACPLF, 2011, 'A hybrid approach to learn with imbalanced classes using evolutionary algorithms', Logic Journal of IGPL, 19, pp. 293 - 293

Prati R; Batista G; Monard M, 2010, 'A survey on graphical methods for classification predictive performance evaluation', Knowledge and Data Engineering, IEEE Transactions on, pp. 1 - 1

Prati RC; Batista GEDAPA; Monard MC, 2008, 'Evaluating classifiers using ROC curves', IEEE Latin America Transactions, 6, pp. 215 - 222, http://dx.doi.org/10.1109/TLA.2008.4609920

Prati RC; Batista GEAPA; Monard MC, 2008, 'Curvas ROC para avaliaç ao de classificadores', Revista IEEE América Latina, 6, pp. 215 - 222

Batista GEAPA; Milaré CR; Prati RC; Monard MC, 2006, 'A Comparison of Methods for Rule Subset Selection Applied to Associative Classification.', Inteligencia artificial: Revista Iberoamericana de Inteligencia Artificial, 10, pp. 29 - 35

Batista G; Prati R; Monard M, 2005, 'Balancing strategies and class overlapping', Advances in Intelligent Data Analysis VI, pp. 741 - 741

Batista GEAPA; Prati RC; Monard MC, 2004, 'A study of the behavior of several methods for balancing machine learning training data', ACM SIGKDD Explorations Newsletter, 6, pp. 20 - 29

Milaré C; Batista G; de Carvalho A; Monard M, 2004, 'Applying genetic and symbolic learning algorithms to extract rules from artificial neural networks', MICAI 2004: Advances in Artificial Intelligence, pp. 833 - 843

Prati R; Batista G; Monard M, 2004, 'Class imbalances versus class overlapping: an analysis of a learning system behavior', MICAI 2004: Advances in Artificial Intelligence, pp. 312 - 321

Batista GEAPA; Monard MC, 2003, 'An analysis of four missing data treatment methods for supervised learning', Applied Artificial Intelligence, 17, pp. 519 - 533

Batista GEAPA; Monard MC, 2003, 'Descriç ao da arquitetura e do projeto do ambiente computacional DISCOVER LEARNING ENVIRONMENT—DLE', Relatório Técnico do ICMC/USP

Batista GEAPA; Monard MC, 2003, 'Experimental comparison of K-nearest neighbour and mean or mode imputation methods with the internal strategies used by C4. 5 and CN2 to treat missing data', University of Sao Paulo

Batista GEAPA; Monard MC, 2002, 'A Study of K-Nearest Neighbour as an Imputation Method.', HIS, 87, pp. 48 - 48

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