10 citations · 10 across the 10 of their papers we have counts for
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How to RETIRE Tabular Data in Favor of Discrete Digital Signal Representation
Paweł Zyblewski, Szymon Wojciechowski
The successes achieved by deep neural networks in computer vision tasks have led in recent years to the emergence of a new research area dubbed Multi-Dimensional Encoding (MDE). Me…
Structuring the Processing Frameworks for Data Stream Evaluation and Application
Joanna Komorniczak, Paweł Ksieniewicz, Paweł Zyblewski
The following work addresses the problem of frameworks for data stream processing that can be used to evaluate the solutions in an environment that resembles real-world application…
Cross-Modality Clustering-based Self-Labeling for Multimodal Data Classification
Paweł Zyblewski, Leandro L. Minku
Technological advances facilitate the ability to acquire multimodal data, posing a challenge for recognition systems while also providing an opportunity to use the heterogeneous na…
Employing Two-Dimensional Word Embedding for Difficult Tabular Data Stream Classification
Paweł Zyblewski
Rapid technological advances are inherently linked to the increased amount of data, a substantial portion of which can be interpreted as data stream, capable of exhibiting the phen…
Active Weighted Aging Ensemble for Drifted Data Stream Classification
Michał Woźniak, Paweł Zyblewski, Paweł Ksieniewicz
One of the significant problems of streaming data classification is the occurrence of concept drift, consisting of the change of probabilistic characteristics of the classification…
stream-learn -- open-source Python library for difficult data stream batch analysis
Paweł Ksieniewicz, Paweł Zyblewski
stream-learn is a Python package compatible with scikit-learn and developed for the drifting and imbalanced data stream analysis. Its main component is a stream generator, which al…