Data stream analysis: Foundations, major tasks and tools von Bahri, Maroua, Bifet, Albert, Gama, João, Gomes, Heitor Murilo, Maniu, Silviu

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Balancing Performance and Energy Consumption of Bagging Ensembles for the Classification of Data Streams in Edge Computing von Cassales, Guilherme, Gomes, Heitor Murilo, Bifet, Albert, Pfahringer, Bernhard, Senger, Hermes

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A Hybrid Sampling Approach for Imbalanced Binary and Multi-Class Data Using Clustering Analysis von Palli, Abdul Sattar, Jaafar, Jafreezal, Hashmani, Manzoor Ahmed, Gomes, Heitor Murilo, Gilal, Abdul Rehman

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Combined Effect of Concept Drift and Class Imbalance on Model Performance During Stream Classification von Sattar Palli, Abdul, Jaafar, Jafreezal, Ahmed Hashmani, Manzoor, Murilo Gomes, Heitor, Alsughayyir, Aeshah, Rehman Gilal, Abdul

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An Experimental Analysis of Drift Detection Methods on Multi-Class Imbalanced Data Streams von Palli, Abdul Sattar, Jaafar, Jafreezal, Gomes, Heitor Murilo, Hashmani, Manzoor Ahmed, Gilal, Abdul Rehman

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Online Machine Learning from Non-stationary Data Streams in the Presence of Concept Drift and Class Imbalance: A Systematic Review von Palli, Abdul Sattar, Jaafar, Jafreezal, Gilal, Abdul Rehman, Alsughayyir, Aeshah, Gomes, Heitor Murilo, Alshanqiti, Abdullah, Omar, Mazni

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Adaptive Prediction Interval for Data Stream Regression von Sun, Yibin, Pfahringer, Bernhard, Murilo Gomes, Heitor, Bifet, Albert

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A Survey on Ensemble Learning for Data Stream Classification von Gomes, Heitor Murilo, Barddal, Jean Paul, Enembreck, Fabrício, Bifet, Albert

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On Dynamic Feature Weighting for Feature Drifting Data Streams von Barddal, Jean Paul, Murilo Gomes, Heitor, Enembreck, Fabrício, Pfahringer, Bernhard, Bifet, Albert

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River: machine learning for streaming data in Python von Montiel, Jacob, Halford, Max, Mastelini, Saulo Martiello, Bolmier, Geoffrey, Sourty, Raphaël, Vaysse, Robin, Zouitine, Adil, Gomes, Heitor Murilo, Read, Jesse, Abdessalem, Talel, Bifet, Albert

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A survey on feature drift adaptation: Definition, benchmark, challenges and future directions von Barddal, Jean Paul, Gomes, Heitor Murilo, Enembreck, Fabrício, Pfahringer, Bernhard

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SeGDroid: An Android malware detection method based on sensitive function call graph learning von Liu, Zhen, Wang, Ruoyu, Japkowicz, Nathalie, Gomes, Heitor Murilo, Peng, Bitao, Zhang, Wenbin

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STUDD: a student–teacher method for unsupervised concept drift detection von Cerqueira, Vitor, Gomes, Heitor Murilo, Bifet, Albert, Torgo, Luis

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SOKNL: A novel way of integrating K-nearest neighbours with adaptive random forest regression for data streams von Sun, Yibin, Pfahringer, Bernhard, Gomes, Heitor Murilo, Bifet, Albert

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Improving the performance of bagging ensembles for data streams through mini-batching von Cassales, Guilherme, Gomes, Heitor, Bifet, Albert, Pfahringer, Bernhard, Senger, Hermes

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LP-ROBIN: Link prediction in dynamic networks exploiting incremental node embedding von Barracchia, Emanuele Pio, Pio, Gianvito, Bifet, Albert, Gomes, Heitor Murilo, Pfahringer, Bernhard, Ceci, Michelangelo

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Fast & Furious: On the modelling of malware detection as an evolving data stream von Ceschin, Fabrício, Botacin, Marcus, Gomes, Heitor Murilo, Pinagé, Felipe, Oliveira, Luiz S., Grégio, André

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Merit-guided dynamic feature selection filter for data streams von Barddal, Jean Paul, Enembreck, Fabrício, Gomes, Heitor Murilo, Bifet, Albert, Pfahringer, Bernhard

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Look At Me, No Replay! SurpriseNet: Anomaly Detection Inspired Class Incremental Learning von Lee, Anton, Zhang, Yaqian, Heitor Murilo Gomes, Bifet, Albert, Pfahringer, Bernhard

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Delayed labelling evaluation for data streams von Grzenda, Maciej, Gomes, Heitor Murilo, Bifet, Albert

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