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

• Evaluating k-NN in the Classification of Data Streams with Concept Drift. arXiv, 2022 (DOI).
• Dynamically Adjusting Diversity in Ensembles for the Classification of Data Streams with Concept Drift. ACM Transactions on Knowledge Discovery from Data, v. 16 (Issue 2), p. 1-20, 2022 (DOI).
• Spectral analysis and optimization of the condition number problem. Computer Physics Communications, v. 258, p. 107587, 2021 (DOI).
• Statistical Tests Ensemble Drift Detector. IEEE Symposium Series on Computational Intelligence (SSCI), Canberra, Australia, p. 1021-1028, 2020 (DOI).
• MOAManager: A tool to support data stream experiments. Software-Practice & Experience, v. 50, p. 325-334, 2020 (DOI).
• An overview and comprehensive comparison of ensembles for concept drift. Information Fusion, v. 52, p. 213-244, 2019 (DOI).
• Online AdaBoost-based methods for multiclass problems. Artificial Intelligence Review, 2019 (DOI).
• A differential evolution based method for tuning concept drift detectors in data streams. Information Sciences, v. 485, p. 376-393, 2019 (DOI).
• A large-scale comparison of concept drift detectors. Information Sciences, v. 452, p. 348-370, 2018 (DOI).
• RDDM: Reactive drift detection method. Expert Systems with Applications, v. 90, p. 344-355, 2017 (DOI).
• A Boosting-like Online Learning Ensemble. International Joint Conference on Neural Networks (IJCNN), Vancouver, BC, Canada, p. 1871, 2016 (DOI).
• Optimizing the Parameters of Drift Detection Methods Using a Genetic Algorithm. International Conference on Tools with Artificial Intelligence (ICTAI), Vietri sul Mare, Italy, p. 1077, 2015 (DOI).
• A Lightweight Concept Drift Detection Ensemble. International Conference on Tools with Artificial Intelligence (ICTAI), Vietri sul Mare, Italy, p. 1061, 2015 (DOI).
• A comparative study on concept drift detectors. Expert Systems with Applications, v. 41, p. 8144-8156, 2014 (DOI).
• Speeding Up Recovery from Concept Drifts. Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD), Nancy, France, v. 8726, p. 179-194, 2014 (DOI).

Additional materials from some published articles can be found here.

Contact

silas[at]silasgarrido.com

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