By Associate Professor Gustavo Batista

Journal articles

Batista GEAPA; Monard MC, 2002, 'K-Nearest Neighbour as Imputation Method: Experimental Results', Technical report, ICMC-USP

Monard MC; Batista GEAPA, 2002, 'Learning with Skewed Class Distributions', Advances in Logic, Artificial Intelligence, and Robotics: LAPTEC 2002, 85, pp. 173 - 173

Batista G; Carvalho A; Monard M, 2000, 'Applying one-sided selection to unbalanced datasets', MICAI 2000: Advances in Artificial Intelligence, pp. 315 - 325

Batista GEAPA, 1997, 'Um ambiente de avaliaçao de algoritmos de aprendizado de máquina utilizando exemplos', Dissertaç ao de Mestrado, ICMC-USP

Conference Papers

Gil MZ; Hu Z; Lyu M; Batista G; Habibi Gharakheili H, 2024, 'Systematic Mapping and Temporal Reasoning of IoT Cyber Risks using Structured Data', in Asian Internet Engineering Conference, AINTEC 2024, pp. 18 - 25, http://dx.doi.org/10.1145/3674213.3674216

Azizi S; Okui N; Nakahara M; Kubota A; Batista G; Gharakheili HH, 2024, 'Poster: Understanding and Managing Changes in IoT Device Behaviors for Reliable Network Traffic Inference', in SIGCOMM Posters and Demos 2024 - Proceedings of the 2024 SIGCOMM Poster and Demo Sessions, Part of: SIGCOMM 2024, pp. 25 - 27, http://dx.doi.org/10.1145/3672202.3673723

Wang H; Zhi W; Batista G; Chandra R, 2024, 'Pedestrian Trajectory Prediction Using Dynamics-based Deep Learning', in Proceedings - IEEE International Conference on Robotics and Automation, pp. 15068 - 15075, http://dx.doi.org/10.1109/ICRA57147.2024.10609993

Perera Y; Batista G; Hu W; Kanhere S; Jha S, 2024, 'SAfER: Simplified Auto-encoder for (Anomalous) Event Recognition', in Proceedings - 2024 20th International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2024, pp. 229 - 233, http://dx.doi.org/10.1109/DCOSS-IoT61029.2024.00041

Serapião ABS; Donyavi Z; Batista G, 2023, 'Ensembles of Classifiers and Quantifiers with Data Fusion for Quantification Learning', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 3 - 17, http://dx.doi.org/10.1007/978-3-031-45275-8_1

Donyavi Z; Serapio A; Batista G, 2023, 'MC-SQ: A Highly Accurate Ensemble for Multi-class Quantification', in 2023 SIAM International Conference on Data Mining, SDM 2023, pp. 622 - 630, http://dx.doi.org/10.1137/1.9781611977653.ch70

Tin D; Shahpasand M; Gharakheili HH; Batista G, 2022, 'Classifying Time-Series of IoT Flow Activity using Deep Learning and Intransitive Features', in International Conference on Software, Knowledge Information, Industrial Management and Applications, SKIMA, pp. 192 - 197, http://dx.doi.org/10.1109/SKIMA57145.2022.10029420

Chen B; Bakhshi A; Batista G; Ng B; Chin TJ, 2022, 'Update Compression for Deep Neural Networks on the Edge', in IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, pp. 3075 - 3085, http://dx.doi.org/10.1109/CVPRW56347.2022.00347

Sharma A; Li J; Mishra D; Batista G; Seneviratne A, 2021, 'Passive WiFi CSI Sensing Based Machine Learning Framework for COVID-Safe Occupancy Monitoring', in 2021 IEEE International Conference on Communications Workshops, ICC Workshops 2021 - Proceedings, Institute of Electrical and Electronics Engineers (IEEE), ELECTR NETWORK, pp. 1 - 6, presented at 2021 IEEE International Conference on Communications Workshops (ICC Workshops), ELECTR NETWORK, 14 June 2021 - 23 June 2021, http://dx.doi.org/10.1109/ICCWorkshops50388.2021.9473673

Da Silva TP; Parmezan ARS; Batista GEAPA, 2021, 'A Graph-Based Spatial Cross-Validation Approach for Assessing Models Learned with Selected Features to Understand Election Results', in Proceedings - 20th IEEE International Conference on Machine Learning and Applications, ICMLA 2021, pp. 909 - 915, http://dx.doi.org/10.1109/ICMLA52953.2021.00150

Maletzke A; Reis DD; Hassan W; Batista G, 2021, 'Accurately Quantifying under Score Variability', in Proceedings - IEEE International Conference on Data Mining, ICDM, pp. 1228 - 1233, http://dx.doi.org/10.1109/ICDM51629.2021.00149

Hassan W; Maletzke A; Batista G, 2021, 'Pitfalls in Quantification Assessment', in CEUR Workshop Proceedings

Rebello G; Hu Y; Thilakarathna K; Batista G; Seneviratne A; Duarte OCMB, 2020, 'Melhorando a Acurácia da Detecção de Lavagem de Dinheiro na Rede Bitcoin', in Anais XXXVIII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos (SBRC 2020), Sociedade Brasileira de Computação, pp. 728 - 741, presented at Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos, http://dx.doi.org/10.5753/sbrc.2020.12321

Jacintho LHM; da Silva TP; Parmezan ARS; de Almeida Prado Alves Batista GE; Batista G, 2020, 'Brazilian Presidential Elections: Analysing Voting Patterns in Time and Space Using a Simple Data Science Pipeline', in Anais do Symposium on Knowledge Discovery, Mining and Learning (KDMiLe 2020), Sociedade Brasileira de Computacao - SB, pp. 217 - 224, presented at Anais do Symposium on Knowledge Discovery, Mining and Learning (KDMiLe 2020), http://dx.doi.org/10.5753/kdmile.2020.11979

Hassan W; Maletzke A; Batista G, 2020, 'Accurately quantifying a billion instances per second', in Proceedings - 2020 IEEE 7th International Conference on Data Science and Advanced Analytics, DSAA 2020, pp. 1 - 10, http://dx.doi.org/10.1109/DSAA49011.2020.00012

Parmezan ARS; Silva DF; Batista GEAPA, 2020, 'A COMBINATION OF LOCAL APPROACHES FOR HIERARCHICAL MUSIC GENRE CLASSIFICATION', in Proceedings of the 21st International Society for Music Information Retrieval Conference, ISMIR 2020, pp. 876 - 883

de Sá JMC; Rossi ALD; Batista GEAPA; Garcia LPF, 2020, 'Algorithm recommendation for data streams', in Proceedings - International Conference on Pattern Recognition, pp. 6073 - 6080, http://dx.doi.org/10.1109/ICPR48806.2021.9411923

Maletzke A; Hassan W; dos Reis D; Batista G, 2020, 'The Importance of the Test Set Size in Quantification Assessment', in IJCAI, IJCAI, YOKOHAMA, pp. 2640 - 2646, presented at Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence Main track, YOKOHAMA, http://dx.doi.org/10.24963/ijcai.2020/366

Tsutsui Da Silva L; Souza VMA; Batista GEAPA, 2019, 'EmbML Tool: Supporting the use of supervised learning algorithms in low-cost embedded systems', in Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI, pp. 1633 - 1637, http://dx.doi.org/10.1109/ICTAI.2019.00238

Maletzke A; dos Reis D; Cherman E; Batista G, 2019, 'DyS: a Framework for Mixture Models in Quantification', in Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19)

Souza V; Pinho T; Batista G, 2018, 'Evaluating stream classifiers with delayed labels information', in Proceedings - 2018 Brazilian Conference on Intelligent Systems, BRACIS 2018, pp. 408 - 413, http://dx.doi.org/10.1109/BRACIS.2018.00077

dos Reis D; Maletzke A; Cherman E; Batista G, 2018, 'One-class quantification', in Joint European Conference on Machine Learning and Knowledge Discovery in Databases, Springer, Dublin, Ireland, pp. 273 - 289, presented at ECML PKDD 2018, Dublin, Ireland, 10 September 2018 - 14 September 2018, http://dx.doi.org/10.1007/978-3-030-10925-7

Silva DF; Batista GEAPA; Keogh E, 2018, 'Large-Scale Similarity-Based Time Series Mining', in Anais do Concurso de Teses e Dissertações da SBC (CTD-SBC), Sociedade Brasileira de Computação - SBC, presented at XXXI Concurso de Teses e Dissertações da SBC, http://dx.doi.org/10.5753/ctd.2018.3656

da Silva TP; Souza VMA; Batista GEAPA; de Arruda Camargo H, 2018, 'A Fuzzy Classifier for Data Streams with Infinitely Delayed Labels', in 23rd Iberoamerican Congress on Pattern Recognition (CIARP)

Moreira dos Reis D; Maletzke A; Silva DF; Batista GEAPA, 2018, 'Classifying and counting with recurrent contexts', in Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp. 1983 - 1992

Silva DF; Batista GEAPA, 2018, 'Elastic time series motifs and discords', in 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA), IEEE, pp. 237 - 242, IEEE

Maletzke A; dos Reis D; Cherman E; Batista G, 2018, 'On the Need of Class Ratio Insensitive Drift Tests for Data Streams', in Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, pp. 110 - 124

Parmezan ARS; Souza VMA; Batista GEAPA, 2018, 'Towards Hierarchical Classification of Data Streams', in 23rd Iberoamerican Congress on Pattern Recognition (CIARP), pp. 314 - 322

dos Reis DM; Maletzke AG; Batista GEAPA, 2018, 'Unsupervised context switch for classification tasks on data streams with recurrent concepts', in Proceedings of the 33rd Annual ACM Symposium on Applied Computing, pp. 518 - 524

Batista GEAPA; Tinós R, 2017, 'Message from program chairs', in Proceedings - 2017 Brazilian Conference on Intelligent Systems, BRACIS 2017, pp. xiv, http://dx.doi.org/10.1109/BRACIS.2017.5

Maletzke AG; dos Reis DM; Batista GEAPA, 2017, 'Quantification in data streams: Initial results', in 2017 Brazilian Conference on Intelligent Systems (BRACIS), IEEE, pp. 43 - 48, IEEE

Giusti R; Silva DF; Batista GEAPA, 2016, 'Improved Time Series Classification with Representation Diversity and SVM', in 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA), IEEE, pp. 1 - 6, presented at 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA), 18 December 2016 - 20 December 2016, http://dx.doi.org/10.1109/icmla.2016.0010

Silva DF; Batista GEAPA; Keogh E, 2016, 'Prefix and Suffix Invariant Dynamic Time Warping', in 2016 IEEE 16th International Conference on Data Mining (ICDM), IEEE, pp. 1209 - 1214, presented at 2016 IEEE 16th International Conference on Data Mining (ICDM), 12 December 2016 - 15 December 2016, http://dx.doi.org/10.1109/icdm.2016.0161

Silva DF; Yeh CCM; Batista GEAPA; Keogh E, 2016, 'SiMPle: Assessing music similarity using subsequences joins', in Proceedings of the 17th International Society for Music Information Retrieval Conference, ISMIR 2016, pp. 23 - 29

Sousa CAR; Batista GEAPA, 2016, 'Constrained Local and Global Consistency for semi-supervised learning', in 2016 23rd International Conference on Pattern Recognition (ICPR), IEEE, pp. 1689 - 1694, IEEE

dos Reis DM; Flach P; Matwin S; Batista G, 2016, 'Fast unsupervised online drift detection using incremental kolmogorov-smirnov test', in Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1545 - 1554

Giusti R; Silva DF; Batista GEAPA, 2016, 'Improved time series classification with representation diversity and svm', in 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA), IEEE, pp. 1 - 6, IEEE

Silva DF; Batista GEAPA; Keogh E; others , 2016, 'On the effect of endpoints on dynamic time warping', in SIGKDD Workshop on Mining and Learning from Time Series II, San Francisco, CA. Association for Computing Machinery-ACM

Silva DF; Batista GEAPA; Keogh E, 2016, 'Prefix and suffix invariant dynamic time warping', in 2016 IEEE 16th International Conference on Data Mining (ICDM), IEEE, pp. 1209 - 1214, IEEE

Silva DF; Batista GEAPA, 2016, 'Speeding up all-pairwise dynamic time warping matrix calculation', in Proceedings of the 2016 SIAM International Conference on Data Mining, Society for Industrial and Applied Mathematics, pp. 837 - 845, Society for Industrial and Applied Mathematics

Parmezan ARS; Batista GEAPA, 2015, 'A study of the use of complexity measures in the similarity search process adopted by knn algorithm for time series prediction', in 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA), IEEE, pp. 45 - 51, IEEE

de Sousa CAR; Souza VMA; Batista GEAPA, 2015, 'An experimental analysis on time series transductive classification on graphs', in 2015 International Joint Conference on Neural Networks (IJCNN), IEEE, pp. 1 - 8, IEEE

Souza VMA; Batista GEAPA; Souza-Filho NE, 2015, 'Automatic classification of drum sounds with indefinite pitch', in 2015 International Joint Conference on Neural Networks (IJCNN), IEEE, pp. 1 - 8, IEEE

Souza VMA; Silva DF; Batista GEAPA; Gama J, 2015, 'Classification of Evolving Data Streams with Infinitely Delayed Labels', in IEEE International Conference on Machine Learning & Applications (ICMLA), pp. 214 - 219

Souza VMA; Silva DF; Gama JA; Batista GEAPA, 2015, 'Data Stream Classification Guided by Clustering on Nonstationary Environments and Extreme Verification Latency', in SIAM International Conference on Data Mining (SDM), pp. 873 - 881

Qi Y; Cinar GT; Souza VMA; Batista GEAPA; Wang Y; Principe JC, 2015, 'Effective insect recognition using a stacked autoencoder with maximum correntropy criterion', in 2015 International Joint Conference on Neural Networks (IJCNN), IEEE, pp. 1 - 7, IEEE

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