DM&ML – poster session papers

  1. 2022, A Twitter Trends Analysis with Hashtags Clustering – Weronika A. Borek-Marciniec, Paweł Ksieniewicz
  2. A neural network with learnable activations for one-sided control limits – Kamil Kmita, Katarzyna Kaczmarek-Majer
  3. An alternative to Transfer Learning in One-class Open Set Recognition – Joanna Komorniczak, Paweł Ksieniewicz
  4. Aqmlator — An auto quantum machine learning e-platform – Tomasz Rybotycki, Piotr Gawron
  5. Clustering Dilemmas – A Study of the Request of Homogenicity within Clusters Versus Diversity Between Clusters –  Mieczysław A. Kłopotek
  6. Combining Multi-objective Evolutionary Undersampling Solutions – Szymon Wojciechowski
  7. Contextual ES-adRNN with Attention Mechanisms for Forecasting – Slawek Smyl, Grzegorz Dudek, Paweł Pełka
  8. Deep Logits Clustering – Paweł Zyblewski, Paweł Ksieniewicz
  9. Detecting and recognizing outliers in non-relational datasets using method based on fuzzy sets – Monika Bartczak, Adam Niewiadomski, Marcin Kacprowiczq
  10. Effectively simulating correlation structure of multidimensional biological datasets – Piotr Stomma, Witold Rudnicki
  11. Emotion detection from tweets as a multi-class problem – Barbara Probierz, Jan Kozak
  12. Frugal ML with InfoFrames – Mateusz Wnuk, Dominik Slezak
  13. Generalization of the weighted TPR-TNR performance metric – Robert Burduk
  14. Graph-Supported Preparation of GIS Machine Learning Datasets – Sebastian Ernst
  15. Hashtag Similarity Based on Laplacian Eigenvalue Spectrum –  Mieczysław A. Kłopotek, Sławomir Wierzchoń, Bartłomiej Starosta
  16. Improving understandability of explanations with a usage of expert knowledge – Maciej mr Szelążek, Szymon Bobek, Grzegorz Nalepa
  17. Integrating EPP Measure with OpenML Repository: Enhancing Meta-Learning Experimentation? –  Katarzyna Woźnica, Marie Anastacio, Przemyslaw Biecek, Jan Van Rijn
  18. Let the STIG find the most relevant features – Radosław Piliszek, Witold Rudnicki
  19. Long-Term Prediction of Multiple Types of Time-Varying Network Traffic Using Chunk-Based Ensemble Learning – Aleksandra Knapińska, Piotr Lechowicz, Weronika T Węgier, Krzysztof Walkowiak
  20. New Voting Schemas for Heterogeneous Ensemble of Classifiers in the Problem of Football Results Prediction – Szymon Głowania, Jan Kozak, Przemysław Juszczuk
  21. On usefulness of dominance relation for selecting counterfactuals from the ensemble of explainers – Jerzy Stefanowski, Mateusz Lango, Ignacy Stępka
  22. Optimized hybrid imbalanced data sampling for decision tree training – Weronika T Węgier, Michał Koziarski, Michal Wozniak
  23. Parametric Monte Carlo Feature Filtering – Krzysztof Mnich, Witold Rudnicki
  24. Revdbscan and flexscan—$O(n\log n)$ clustering algorithms – Norbert Jankowski
  25. Schauder fixed-point theorem implications in long-range prediction in Cloud computing environments – Krzysztof Marek Pałczyński, Jakub Kosterna, Tomasz Andrysiak
  26. Seasonal Change-Point Detection Algorithm – Krzysztof Marek Pałczyński, Wiktor Kurek, Tomasz Andrysiak
  27. Stability of the ensemble classification model using aggregation functions for microarray datasets – Wojciech Gałka, Urszula Bentkowska, Marcin Mrukowicz
  28. Towards Detection of Unknown Polymorphic Patterns Using Prior Knowledge – Przemysław Kucharski, Krzysztof Slot
  29. Users’ intentions and preferences in AI-assisted database querying: a passive and active account for context – Janusz Kacprzyk, Slawomir Zadrozny