Jerzy Stefanowski

ORCID

Publication Activity (10 Years)

Years Active: 1992-2024
Publications (10 Years): 47

Top Venues

Publications

Jacek Karolczak, Jerzy Stefanowski
A-PETE: Adaptive Prototype Explanations of Tree Ensembles. CoRR (2024)
Patryk Wielopolski, Oleksii Furman, Jerzy Stefanowski, Maciej Zieba
Unifying Perspectives: Plausible Counterfactual Explanations on Global, Group-wise, and Local Levels. CoRR (2024)
Ignacy Stepka, Mateusz Lango, Jerzy Stefanowski
Multi-criteria approach for selecting an explanation from the set of counterfactuals produced by an ensemble of explainers. CoRR (2024)
Ignacy Stepka, Mateusz Lango, Jerzy Stefanowski
A multi-criteria approach for selecting an explanation from the set of counterfactuals produced by an ensemble of explainers. Int. J. Appl. Math. Comput. Sci. 34 (1) (2024)
Patryk Wielopolski, Oleksii Furman, Jerzy Stefanowski, Maciej Zieba
Probabilistically Plausible Counterfactual Explanations with Normalizing Flows. CoRR (2024)
Dariusz Brzezinski, Julia Stachowiak, Jerzy Stefanowski, Izabela Szczech, Robert Susmaga, Sofya Aksenyuk, Uladzimir Ivashka, Oleksandr Yasinskyi
Properties of Fairness Measures in the Context of Varying Class Imbalance and Protected Group Ratios. ACM Trans. Knowl. Discov. Data 18 (7) (2024)
Dariusz Brzezinski, Julia Stachowiak, Jerzy Stefanowski, Izabela Szczech, Robert Susmaga, Sofya Aksenyuk, Uladzimir Ivashka, Oleksandr Yasinskyi
Properties of Fairness Measures in the Context of Varying Class Imbalance and Protected Group Ratios. IEEE Trans. Knowl. Data Eng. 18 (7) (2024)
Damian Horna, Mateusz Lango, Jerzy Stefanowski
Deep Similarity Learning Loss Functions in Data Transformation for Class Imbalance. CoRR (2023)
Jakub Raczynski, Mateusz Lango, Jerzy Stefanowski
The Problem of Coherence in Natural Language Explanations of Recommendations. CoRR (2023)
Riccardo Albertoni, Sara Colantonio, Piotr Skrzypczynski, Jerzy Stefanowski
Reproducibility of Machine Learning: Terminology, Recommendations and Open Issues. CoRR (2023)
Jerzy Stefanowski
Multi-criteria Approaches to Explaining Black Box Machine Learning Models. ACIIDS (2) (2023)
Damian Horna, Mateusz Lango, Jerzy Stefanowski
Deep Similarity Learning Loss Functions in Data Transformation for Class Imbalance. LIDTA (2023)
Marcin Korcz, Dawid Plaskowski, Mateusz Politycki, Jerzy Stefanowski, Alex Terentowicz
PIQARD System for Experimenting and Testing Language Models with Prompting Strategies. ECML/PKDD (7) (2023)
Jakub Raczynski, Mateusz Lango, Jerzy Stefanowski
The Problem of Coherence in Natural Language Explanations of Recommendations. ECAI (2023)
Agnieszka Lipska, Jerzy Stefanowski
The Influence of Multiple Classes on Learning Online Classifiers from Imbalanced and Concept Drifting Data Streams. CoRR (2022)
Witold Andrzejewski, Jedrzej Potoniec, Maciej Drozdowski, Jerzy Stefanowski, Robert Wrembel, Pawel Stapf
Quality Versus Speed in Energy Demand Prediction - Experience Report from an R &D project. DEXA (1) (2022)
Witold Andrzejewski, Jedrzej Potoniec, Maciej Drozdowski, Jerzy Stefanowski, Robert Wrembel, Pawel Stapf
Quality versus speed in energy demand prediction for district heating systems. CoRR (2022)
Agnieszka Lipska, Jerzy Stefanowski
The Influence of Multiple Classes on Learning from Imbalanced Data Streams. LIDTA (2022)
Mateusz Lango, Jerzy Stefanowski
What makes multi-class imbalanced problems difficult? An experimental study. Expert Syst. Appl. 199 (2022)
Jerzy Stefanowski
Classification of Multi-class Imbalanced Data: Data Difficulty Factors and Selected Methods for Improving Classifiers. IJCRS (2021)
Maria Naklicka, Jerzy Stefanowski
Two Ways of Extending BRACID Rule-based Classifiers for Multi-class Imbalanced Data. LIDTA@ECML/PKDD (2021)
Dariusz Brzezinski, Leandro L. Minku, Tomasz Pewinski, Jerzy Stefanowski, Artur Szumaczuk
The impact of data difficulty factors on classification of imbalanced and concept drifting data streams. Knowl. Inf. Syst. 63 (6) (2021)
Piotr Janiszewski, Mateusz Lango, Jerzy Stefanowski
Time Aspect in Making an Actionable Prediction of a Conversation Breakdown. ECML/PKDD (5) (2021)
Kamil Plucinski, Mateusz Lango, Jerzy Stefanowski
Prototypical Convolutional Neural Network for a Phrase-Based Explanation of Sentiment Classification. PKDD/ECML Workshops (1) (2021)
Dariusz Brzezinski, Jerzy Stefanowski, Robert Susmaga, Izabela Szczech
On the Dynamics of Classification Measures for Imbalanced and Streaming Data. IEEE Trans. Neural Networks Learn. Syst. 31 (8) (2020)
Jacek Grycza, Damian Horna, Hanna Klimczak, Mateusz Lango, Kamil Plucinski, Jerzy Stefanowski
multi-imbalance: Open Source Python Toolbox for Multi-class Imbalanced Classification. ECML/PKDD (5) (2020)
Malgorzata Janicka, Mateusz Lango, Jerzy Stefanowski
Using Information on Class Interrelations to Improve Classification of Multiclass Imbalanced Data: A New Resampling Algorithm. Int. J. Appl. Math. Comput. Sci. 29 (4) (2019)
Jerzy Blaszczynski, Jerzy Stefanowski
Local Data Characteristics in Learning Classifiers from Imbalanced Data. Advances in Data Analysis with Computational Intelligence Methods (2018)
Dariusz Brzezinski, Jerzy Stefanowski, Robert Susmaga, Izabela Szczech
Visual-based analysis of classification measures and their properties for class imbalanced problems. Inf. Sci. 462 (2018)
Mateusz Lango, Jerzy Stefanowski
Multi-class and feature selection extensions of Roughly Balanced Bagging for imbalanced data. J. Intell. Inf. Syst. 50 (1) (2018)
Mateusz Lango, Dariusz Brzezinski, Jerzy Stefanowski
ImWeights: Classifying Imbalanced Data Using Local and Neighborhood Information. LIDTA@ECML/PKDD (2018)
Jerzy Blaszczynski, Jerzy Stefanowski
Actively Balanced Bagging for Imbalanced Data. ISMIS (2017)
Dariusz Brzezinski, Jerzy Stefanowski, Robert Susmaga, Izabela Szczech
Visual-Based Analysis of Classification Measures with Applications to Imbalanced Data. CoRR (2017)
Bartosz Krawczyk, Leandro L. Minku, João Gama, Jerzy Stefanowski, Michal Wozniak
Ensemble learning for data stream analysis: A survey. Inf. Fusion 37 (2017)
Szymon Wojciechowski, Szymon Wilk, Jerzy Stefanowski
An Algorithm for Selective Preprocessing of Multi-class Imbalanced Data. CORES (2017)
Mateusz Lango, Krystyna Napierala, Jerzy Stefanowski
Evaluating Difficulty of Multi-class Imbalanced Data. ISMIS (2017)
Dariusz Brzezinski, Jerzy Stefanowski
Prequential AUC: properties of the area under the ROC curve for data streams with concept drift. Knowl. Inf. Syst. 52 (2) (2017)
Dariusz Brzezinski, Jerzy Stefanowski, Robert Susmaga, Izabela Szczech
Tetrahedron: Barycentric Measure Visualizer. ECML/PKDD (3) (2017)
Mateusz Lango, Dariusz Brzezinski, Sebastian Firlik, Jerzy Stefanowski
Discovering Minority Sub-clusters and Local Difficulty Factors from Imbalanced Data. DS (2017)
Jerzy Stefanowski, Krzysztof Krawiec, Robert Wrembel
Exploring complex and big data. Int. J. Appl. Math. Comput. Sci. 27 (4) (2017)
Dariusz Brzezinski, Jerzy Stefanowski
Ensemble Diversity in Evolving Data Streams. DS (2016)
Jerzy Blaszczynski, Jerzy Stefanowski, Roman Slowinski
Consistency Driven Feature Subspace Aggregating for Ordinal Classification. IJCRS (2016)
Krystyna Napierala, Jerzy Stefanowski, Izabela Szczech
Increasing the Interpretability of Rules Induced from Imbalanced Data by Using Bayesian Confirmation Measures. NFMCP@PKDD/ECML (2016)
Szymon Wilk, Jerzy Stefanowski, Szymon Wojciechowski, Ken J. Farion, Wojtek Michalowski
Application of Preprocessing Methods to Imbalanced Clinical Data: An Experimental Study. ITIB (1) (2016)
Mateusz Lango, Dariusz Brzezinski, Jerzy Stefanowski
PUT at SemEval-2016 Task 4: The ABC of Twitter Sentiment Analysis. SemEval@NAACL-HLT (2016)
Krystyna Napierala, Jerzy Stefanowski
Types of minority class examples and their influence on learning classifiers from imbalanced data. J. Intell. Inf. Syst. 46 (3) (2016)
Krystyna Napierala, Jerzy Stefanowski
Post-processing of BRACID Rules Induced from Imbalanced Data. Fundam. Informaticae 148 (1-2) (2016)
José A. Sáez, Julián Luengo, Jerzy Stefanowski, Francisco Herrera
SMOTE-IPF: Addressing the noisy and borderline examples problem in imbalanced classification by a re-sampling method with filtering. Inf. Sci. 291 (2015)
Jerzy Blaszczynski, Jerzy Stefanowski
Neighbourhood sampling in bagging for imbalanced data. Neurocomputing 150 (2015)
Jerzy Stefanowski
On Properties of Undersampling Bagging and Its Extensions for Imbalanced Data. CORES (2015)
Krystyna Napierala, Jerzy Stefanowski
Addressing imbalanced data with argument based rule learning. Expert Syst. Appl. 42 (24) (2015)
Bartosz Krawczyk, Jerzy Stefanowski, Michal Wozniak
Data stream classification and big data analytics. Neurocomputing 150 (2015)
Jerzy Stefanowski
Adaptive Ensembles for Evolving Data Streams - Combining Block-Based and Online Solutions. NFMCP (2015)
Mateusz Lango, Jerzy Stefanowski
The Usefulness of Roughly Balanced Bagging for Complex and High-Dimensional Imbalanced Data. NFMCP (2015)
Krystyna Napierala, Jerzy Stefanowski
Abstaining in rule set bagging for imbalanced data. Log. J. IGPL 23 (3) (2015)
Jerzy Stefanowski, Krystyna Napierala, Malgorzata Trzcielinska
Local Characteristics of Minority Examples in Pre-processing of Imbalanced Data. ISMIS (2014)
Jerzy Stefanowski, Alfredo Cuzzocrea, Dominik Slezak
Processing and mining complex data streams. Inf. Sci. 285 (2014)
José A. Sáez, Julián Luengo, Jerzy Stefanowski, Francisco Herrera
Managing Borderline and Noisy Examples in Imbalanced Classification by Combining SMOTE with Ensemble Filtering. IDEAL (2014)
Georg Krempl, Indre Zliobaite, Dariusz Brzezinski, Eyke Hüllermeier, Mark Last, Vincent Lemaire, Tino Noack, Ammar Shaker, Sonja Sievi, Myra Spiliopoulou, Jerzy Stefanowski
Open challenges for data stream mining research. SIGKDD Explor. 16 (1) (2014)
Magdalena Deckert, Jerzy Stefanowski
RILL: Algorithm for Learning Rules from Streaming Data with Concept Drift. ISMIS (2014)
Dariusz Brzezinski, Jerzy Stefanowski
Prequential AUC for Classifier Evaluation and Drift Detection in Evolving Data Streams. NFMCP (2014)
Dariusz Brzezinski, Jerzy Stefanowski
Reacting to Different Types of Concept Drift: The Accuracy Updated Ensemble Algorithm. IEEE Trans. Neural Networks Learn. Syst. 25 (1) (2014)
Jerzy Stefanowski
The Impact of Local Data Characteristics on Learning from Imbalanced Data. RSEISP (2014)
Dariusz Brzezinski, Jerzy Stefanowski
Combining block-based and online methods in learning ensembles from concept drifting data streams. Inf. Sci. 265 (2014)
Jerzy Blaszczynski, Jerzy Stefanowski, Lukasz Idkowiak
Extending Bagging for Imbalanced Data. CORES (2013)
Krystyna Napierala, Jerzy Stefanowski
Modifications of Classification Strategies in Rule Set Based Bagging for Imbalanced Data. HAIS (2) (2012)
Jerzy Blaszczynski, Magdalena Deckert, Jerzy Stefanowski, Szymon Wilk
IIvotes ensemble for imbalanced data. Intell. Data Anal. 16 (5) (2012)
Krystyna Napierala, Jerzy Stefanowski
BRACID: a comprehensive approach to learning rules from imbalanced data. J. Intell. Inf. Syst. 39 (2) (2012)
Krystyna Napierala, Jerzy Stefanowski
Identification of Different Types of Minority Class Examples in Imbalanced Data. HAIS (2) (2012)
Magdalena Deckert, Jerzy Stefanowski
Comparing Block Ensembles for Data Streams with Concept Drift. ADBIS Workshops (2012)
Tomasz Maciejewski, Jerzy Stefanowski
Local neighbourhood extension of SMOTE for mining imbalanced data. CIDM (2011)
Dariusz Brzezinski, Jerzy Stefanowski
Accuracy Updated Ensemble for Data Streams with Concept Drift. HAIS (2) (2011)
Jerzy Blaszczynski, Roman Slowinski, Jerzy Stefanowski
Ordinal Classification with Monotonicity Constraints by Variable Consistency Bagging. RSCTC (2010)
Jerzy Blaszczynski, Magdalena Deckert, Jerzy Stefanowski, Szymon Wilk
Integrating Selective Pre-processing of Imbalanced Data with Ivotes Ensemble. RSCTC (2010)
Jerzy Blaszczynski, Roman Slowinski, Jerzy Stefanowski
Variable Consistency Bagging Ensembles. Trans. Rough Sets 11 (2010)
Krystyna Napierala, Jerzy Stefanowski, Szymon Wilk
Learning from Imbalanced Data in Presence of Noisy and Borderline Examples. RSCTC (2010)
Krystyna Napierala, Jerzy Stefanowski
Argument Based Generalization of MODLEM Rule Induction Algorithm. RSCTC (2010)
Jerzy Blaszczynski, Jerzy Stefanowski, Magdalena Zajac
Ensembles of Abstaining Classifiers Based on Rule Sets. ISMIS (2009)
Jerzy Stefanowski, Radoslaw Z. Ziembinski
An experimental evaluation of two approaches to mining context based sequential patterns. Control. Cybern. 38 (1) (2009)
Jerzy Stefanowski, Szymon Wilk
Selective Pre-processing of Imbalanced Data for Improving Classification Performance. DaWaK (2008)
Jerzy Stefanowski
On Combined Classifiers, Rule Induction and Rough Sets. Trans. Rough Sets 6 (2007)
Jerzy Stefanowski
Combining Answers of Sub-classifiers in the Bagging-Feature Ensembles. RSEISP (2007)
Salvatore Greco, Roman Slowinski, Jerzy Stefanowski
Evaluating Importance of Conditions in the Set of Discovered Rules. RSFDGrC (2007)
Jerzy Stefanowski, Dawid Weiss
Comprehensible and Accurate Cluster Labels in Text Clustering. RIAO (2007)
Jerzy Stefanowski, Szymon Wilk
Rough Sets for Handling Imbalanced Data: Combining Filtering and Rule-based Classifiers. Fundam. Informaticae 72 (1-3) (2006)
Mariusz Flasinski, Edward Nawarecki, Lech Polkowski, Robert Schaefer, Jerzy Stefanowski, Zbigniew Suraj
Preface. Fundam. Informaticae 71 (1) (2006)
Jerzy Stefanowski
An Empirical Study of Using Rule Induction and Rough Sets to Software Cost Estimation. Fundam. Informaticae 71 (1) (2006)
Jerzy Stefanowski, Marcin Zienkowicz
Classification of Polish Email Messages: Experiments with Various Data Representations. ISMIS (2006)
Jerzy Stefanowski, Radoslaw Z. Ziembinski
Mining Context Based Sequential Patterns. AWIC (2005)
Jerzy W. Grzymala-Busse, Jerzy Stefanowski, Szymon Wilk
A Comparison of Two Approaches to Data Mining from Imbalanced Data. J. Intell. Manuf. 16 (6) (2005)
Jerzy Stefanowski, Slawomir Nowaczyk
On Using Rule Induction in Multiple Classifiers with a Combiner Aggregation Strategy. ISDA (2005)
Jerzy Zaluski, Renata Szoszkiewicz, Jerzy Krysinski, Jerzy Stefanowski
Rough Set Theory and Decision Rules in Data Analysis of Breast Cancer Patients. Trans. Rough Sets 1 (2004)
Jerzy Stefanowski
-Classifiers Based on Rules Induced by MODLEM. Rough Sets and Current Trends in Computing (2004)
Jerzy Stefanowski
An experimental evaluation of improving rule based classifiers with two approaches that change representations of learning examples. Eng. Appl. Artif. Intell. 17 (4) (2004)
Salvatore Greco, Roman Slowinski, Jerzy Stefanowski, Marcin Zurawski
Incremental versus Non-incremental Rule Induction for Multicriteria Classification. Trans. Rough Sets 2 (2004)
Roman Pindur, Robert Susmaga, Jerzy Stefanowski
Hyperplane Aggregation of Dominance Decision Rules. Fundam. Informaticae 61 (2) (2004)
Stanislaw Osinski, Jerzy Stefanowski, Dawid Weiss
Lingo: Search Results Clustering Algorithm Based on Singular Value Decomposition. Intelligent Information Systems (2004)
Jerzy W. Grzymala-Busse, Jerzy Stefanowski, Szymon Wilk
A Comparison of Two Approaches to Data Mining from Imbalanced Data. KES (2004)
Jerzy Stefanowski, Marcin Zurawski
Incremental Rule Induction for Multicriteria and Multiattribute Classification. IIS (2003)
Dawid Weiss, Jerzy Stefanowski
Web Search Results Clustering in Polish: Experimental Evaluation of Carrot. IIS (2003)

Jerzy Stefanowski.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Jerzy Stefanowski