About
I’m a Ph.D. in Computer Science from Universidade Federal de Pernambuco (CIn-UFPE). My research area is in Machine Learning, with special interest in Online Learning and Concept Drift.
Publications
- A comparative study on concept drift detectors. Expert Systems with Applications 41 (18), 2014 (Scholar) · 270 citations
- RDDM: Reactive drift detection method. Expert Systems with Applications 90, 2017 (Scholar) · 255 citations
- A large-scale comparison of concept drift detectors. Information Sciences 451, 2018 (Scholar) · 218 citations
- An overview and comprehensive comparison of ensembles for concept drift. Information Fusion 52, 2019 (Scholar) · 112 citations
- A boosting-like online learning ensemble. 2016 International Joint Conference on Neural Networks (IJCNN), 2016 (Scholar) · 81 citations
- A lightweight concept drift detection ensemble. 2015 IEEE 27th International Conference on Tools with Artificial …, 2015 (Scholar) · 77 citations
- Speeding up recovery from concept drifts. Machine Learning and Knowledge Discovery in Databases: European Conference …, 2014 (Scholar) · 65 citations
- Online adaboost-based methods for multiclass problems. Artificial Intelligence Review 53 (2), 2020 (Scholar) · 51 citations
- A differential evolution based method for tuning concept drift detectors in data streams. Information Sciences 485, 2019 (Scholar) · 36 citations
- Optimizing the parameters of drift detection methods using a genetic algorithm. 2015 IEEE 27th International Conference on Tools with Artificial …, 2015 (Scholar) · 25 citations
- Dynamically Adjusting Diversity in Ensembles for the Classification of Data Streams with Concept Drift. ACM Transactions on Knowledge Discovery from Data (TKDD) 16 (2), 2021 (Scholar) · 16 citations
- MOAManager: A tool to support data stream experiments. Software: Practice and Experience 50 (4), 2020 (Scholar) · 13 citations
- Spectral analysis and optimization of the condition number problem. Computer Physics Communications 258, 2021 (Scholar) · 7 citations
- Statistical tests ensemble drift detector. 2020 IEEE Symposium Series on Computational Intelligence (SSCI), 2020 (Scholar) · 5 citations
- Evaluating k-NN in the Classification of Data Streams with Concept Drift. arXiv preprint arXiv:2210.03119, 2022 (Scholar) · 3 citations
- Enhancing Semi-Supervised Learning with Concept Drift Detection and Self-Training: A Study on Classifier Diversity and Performance. IEEE Access, 2025 (Scholar) · 3 citations
- Paired k-NN learners with dynamically adjusted number of neighbors for classification of drifting data streams. Knowledge and Information Systems 65 (4), 2023 (Scholar) · 2 citations
- Avaliação criteriosa dos algoritmos de detecção de concept drifts. **, 2015 (Scholar) · 1 citation
- Quantifying Webpage Performance: A Comparative Analysis of TCP/IP and QUIC Communication Protocols for Improved Efficiency. Data 8 (8), 2023 (Scholar) · 1 citation
- Experimenting with Supervised Drift Detectors in Semi-supervised Learning. 2023 IEEE Symposium Series on Computational Intelligence (SSCI), 2023 (Scholar) · 1 citation
- Online boosting para problemas multiclasse. **, 2019 (Scholar)
- Evaluating k-NN in the Classification of Data Streams with Concept Drift. arXiv e-prints, 2022 (Scholar)
- Stock Price Movement Prediction based on Optimized Traditional Machine Learning Models. 2023 IEEE Symposium Series on Computational Intelligence (SSCI), 2023 (Scholar)
- Features and Classes Drift Detector to Deal with Imbalanced Data Streams. 2023 IEEE Symposium Series on Computational Intelligence (SSCI), 2023 (Scholar)
Additional materials from some published articles can be found here.
silas[at]silasgarrido.com
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