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ORCIDJerzy Stefanowski
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- affiliation: Poznan University of Technology, Poland
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Journal Articles
- 2024
[j43]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)- [j42]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): 170 (2024) - 2022
- [j41]Mateusz Lango, Jerzy Stefanowski:
What makes multi-class imbalanced problems difficult? An experimental study. Expert Syst. Appl. 199: 116962 (2022) - 2021
- [j40]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): 1429-1469 (2021) - 2020
- [j39]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): 2868-2878 (2020) - 2019
- [j38]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): 769-781 (2019) - 2018
- [j37]Dariusz Brzezinski, Jerzy Stefanowski, Robert Susmaga, Izabela Szczech:
Visual-based analysis of classification measures and their properties for class imbalanced problems. Inf. Sci. 462: 242-261 (2018) - [j36]Mateusz Lango, Jerzy Stefanowski:
Multi-class and feature selection extensions of Roughly Balanced Bagging for imbalanced data. J. Intell. Inf. Syst. 50(1): 97-127 (2018) - 2017
- [j35]Jerzy Stefanowski, Krzysztof Krawiec, Robert Wrembel:
Exploring complex and big data. Int. J. Appl. Math. Comput. Sci. 27(4): 669-679 (2017) - [j34]Bartosz Krawczyk, Leandro L. Minku, João Gama, Jerzy Stefanowski, Michal Wozniak:
Ensemble learning for data stream analysis: A survey. Inf. Fusion 37: 132-156 (2017) - [j33]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): 531-562 (2017) - 2016
- [j32]Krystyna Napierala, Jerzy Stefanowski:
Post-processing of BRACID Rules Induced from Imbalanced Data. Fundam. Informaticae 148(1-2): 51-64 (2016) - [j31]Krystyna Napierala, Jerzy Stefanowski:
Types of minority class examples and their influence on learning classifiers from imbalanced data. J. Intell. Inf. Syst. 46(3): 563-597 (2016) - 2015
- [j30]Krystyna Napierala, Jerzy Stefanowski:
Addressing imbalanced data with argument based rule learning. Expert Syst. Appl. 42(24): 9468-9481 (2015) - [j29]Krystyna Napierala, Jerzy Stefanowski:
Abstaining in rule set bagging for imbalanced data. Log. J. IGPL 23(3): 421-430 (2015) - [j28]Bartosz Krawczyk, Jerzy Stefanowski, Michal Wozniak:
Data stream classification and big data analytics. Neurocomputing 150: 238-239 (2015) - [j27]Jerzy Blaszczynski, Jerzy Stefanowski:
Neighbourhood sampling in bagging for imbalanced data. Neurocomputing 150: 529-542 (2015) - [j26]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: 184-203 (2015) - 2014
- [j25]Dariusz Brzezinski, Jerzy Stefanowski:
Combining block-based and online methods in learning ensembles from concept drifting data streams. Inf. Sci. 265: 50-67 (2014) - [j24]Jerzy Stefanowski, Alfredo Cuzzocrea, Dominik Slezak:
Processing and mining complex data streams. Inf. Sci. 285: 63-65 (2014) - [j23]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): 1-10 (2014) - [j22]Dariusz Brzezinski, Jerzy Stefanowski:
Reacting to Different Types of Concept Drift: The Accuracy Updated Ensemble Algorithm. IEEE Trans. Neural Networks Learn. Syst. 25(1): 81-94 (2014) - 2012
- [j21]Jerzy Blaszczynski, Magdalena Deckert, Jerzy Stefanowski, Szymon Wilk:
IIvotes ensemble for imbalanced data. Intell. Data Anal. 16(5): 777-801 (2012) - [j20]Krystyna Napierala, Jerzy Stefanowski:
BRACID: a comprehensive approach to learning rules from imbalanced data. J. Intell. Inf. Syst. 39(2): 335-373 (2012) - 2010
- [j19]Jerzy Blaszczynski, Roman Slowinski, Jerzy Stefanowski:
Variable Consistency Bagging Ensembles. Trans. Rough Sets 11: 40-52 (2010) - 2009
- [j18]Jerzy Stefanowski, Radoslaw Z. Ziembinski:
An experimental evaluation of two approaches to mining context based sequential patterns. Control. Cybern. 38(1): 27-45 (2009) - 2007
- [j17]Jerzy Stefanowski:
On Combined Classifiers, Rule Induction and Rough Sets. Trans. Rough Sets 6: 329-350 (2007) - 2006
- [j16]Mariusz Flasinski, Edward Nawarecki, Lech Polkowski, Robert Schaefer, Jerzy Stefanowski, Zbigniew Suraj:
Preface. Fundam. Informaticae 71(1) (2006) - [j15]Jerzy Stefanowski:
An Empirical Study of Using Rule Induction and Rough Sets to Software Cost Estimation. Fundam. Informaticae 71(1): 63-82 (2006) - [j14]Jerzy Stefanowski, Szymon Wilk:
Rough Sets for Handling Imbalanced Data: Combining Filtering and Rule-based Classifiers. Fundam. Informaticae 72(1-3): 379-391 (2006) - 2005
- [j13]Jerzy W. Grzymala-Busse, Jerzy Stefanowski, Szymon Wilk:
A Comparison of Two Approaches to Data Mining from Imbalanced Data. J. Intell. Manuf. 16(6): 565-573 (2005) - 2004
- [j12]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): 439-445 (2004) - [j11]Roman Pindur, Robert Susmaga, Jerzy Stefanowski:
Hyperplane Aggregation of Dominance Decision Rules. Fundam. Informaticae 61(2): 117-137 (2004) - [j10]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: 375-391 (2004) - [j9]Salvatore Greco, Roman Slowinski, Jerzy Stefanowski, Marcin Zurawski:
Incremental versus Non-incremental Rule Induction for Multicriteria Classification. Trans. Rough Sets 2: 33-53 (2004) - 2002
- [j8]Krzysztof Slowinski, Jerzy Stefanowski, Dariusz Siwinski:
Application of Rule Induction and Rough Sets to Verification of Magnetic Resonance Diagnosis. Fundam. Informaticae 53(3-4): 345-363 (2002) - 2001
- [j7]Jerzy Stefanowski, Alexis Tsoukiàs:
Incomplete Information Tables and Rough Classification. Comput. Intell. 17(3): 545-566 (2001) - [j6]Jerzy Stefanowski, Daniel Vanderpooten:
Induction of decision rules in classification and discovery-oriented perspectives. Int. J. Intell. Syst. 16(1): 13-27 (2001) - [j5]Jerzy W. Grzymala-Busse, Jerzy Stefanowski:
Three discretization methods for rule induction. Int. J. Intell. Syst. 16(1): 29-38 (2001) - [j4]Jerzy Stefanowski, Szymon Wilk:
Evaluating business credit risk by means of approach-integrating decision rules and case-based learning. Intell. Syst. Account. Finance Manag. 10(2): 97-114 (2001) - 1997
- [j3]Jacek Jelonek, Jerzy Stefanowski:
Feature subset selection for classification of histological images. Artif. Intell. Medicine 9(3): 227-239 (1997) - 1996
- [j2]Roman Slowinski, Jerzy Stefanowski:
Rough-Set Reasoning about Uncertain Data. Fundam. Informaticae 27(2/3): 229-243 (1996) - [j1]Jerzy W. Grzymala-Busse, Jerzy Stefanowski, Wojciech Ziarko:
Rough Sets: Facts Versus Misconceptions. Informatica (Slovenia) 20(4) (1996)
Conference and Workshop Papers
- 2024
- [c73]Patryk Wielopolski, Oleksii Furman, Jerzy Stefanowski, Maciej Zieba:
Probabilistically Plausible Counterfactual Explanations with Normalizing Flows. ECAI 2024: 954-961 - [c72]Natalia Wojak-Strzelecka, Szymon Bobek, Grzegorz J. Nalepa, Jerzy Stefanowski:
Towards Differentiating Between Failures and Domain Shifts in Industrial Data Streams. HAII5.0@ECAI 2024 - 2023
- [c71]Jerzy Stefanowski:
Multi-criteria Approaches to Explaining Black Box Machine Learning Models. ACIIDS (2) 2023: 195-208 - [c70]Jakub Raczynski, Mateusz Lango, Jerzy Stefanowski:
The Problem of Coherence in Natural Language Explanations of Recommendations. ECAI 2023: 1922-1929 - [c69]Damian Horna, Mateusz Lango, Jerzy Stefanowski:
Deep Similarity Learning Loss Functions in Data Transformation for Class Imbalance. LIDTA 2023: 1-15 - [c68]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: 320-323 - 2022
- [c67]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: 447-452 - [c66]Agnieszka Lipska, Jerzy Stefanowski:
The Influence of Multiple Classes on Learning from Imbalanced Data Streams. LIDTA 2022: 187-198 - 2021
- [c65]Maria Naklicka, Jerzy Stefanowski:
Two Ways of Extending BRACID Rule-based Classifiers for Multi-class Imbalanced Data. LIDTA@ECML/PKDD 2021: 90-103 - [c64]Piotr Janiszewski, Mateusz Lango, Jerzy Stefanowski:
Time Aspect in Making an Actionable Prediction of a Conversation Breakdown. ECML/PKDD (5) 2021: 351-364 - [c63]Kamil Plucinski, Mateusz Lango, Jerzy Stefanowski:
Prototypical Convolutional Neural Network for a Phrase-Based Explanation of Sentiment Classification. PKDD/ECML Workshops (1) 2021: 457-472 - [c62]Jerzy Stefanowski:
Classification of Multi-class Imbalanced Data: Data Difficulty Factors and Selected Methods for Improving Classifiers. IJCRS 2021: 57-72 - 2020
- [c61]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: 546-549 - 2018
- [c60]Jerzy Blaszczynski, Jerzy Stefanowski:
Local Data Characteristics in Learning Classifiers from Imbalanced Data. Advances in Data Analysis with Computational Intelligence Methods 2018: 51-85 - [c59]Mateusz Lango, Dariusz Brzezinski, Jerzy Stefanowski:
ImWeights: Classifying Imbalanced Data Using Local and Neighborhood Information. LIDTA@ECML/PKDD 2018: 95-109 - 2017
- [c58]Szymon Wojciechowski, Szymon Wilk, Jerzy Stefanowski:
An Algorithm for Selective Preprocessing of Multi-class Imbalanced Data. CORES 2017: 238-247 - [c57]Mateusz Lango, Dariusz Brzezinski, Sebastian Firlik, Jerzy Stefanowski:
Discovering Minority Sub-clusters and Local Difficulty Factors from Imbalanced Data. DS 2017: 324-339 - [c56]Jerzy Blaszczynski, Jerzy Stefanowski:
Actively Balanced Bagging for Imbalanced Data. ISMIS 2017: 271-281 - [c55]Mateusz Lango, Krystyna Napierala, Jerzy Stefanowski:
Evaluating Difficulty of Multi-class Imbalanced Data. ISMIS 2017: 312-322 - [c54]Dariusz Brzezinski, Jerzy Stefanowski, Robert Susmaga, Izabela Szczech:
Tetrahedron: Barycentric Measure Visualizer. ECML/PKDD (3) 2017: 419-422 - 2016
- [c53]Dariusz Brzezinski, Jerzy Stefanowski:
Ensemble Diversity in Evolving Data Streams. DS 2016: 229-244 - [c52]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: 503-515 - [c51]Krystyna Napierala, Jerzy Stefanowski, Izabela Szczech:
Increasing the Interpretability of Rules Induced from Imbalanced Data by Using Bayesian Confirmation Measures. NFMCP@PKDD/ECML 2016: 84-98 - [c50]Jerzy Blaszczynski, Jerzy Stefanowski, Roman Slowinski:
Consistency Driven Feature Subspace Aggregating for Ordinal Classification. IJCRS 2016: 580-589 - [c49]Mateusz Lango, Dariusz Brzezinski, Jerzy Stefanowski:
PUT at SemEval-2016 Task 4: The ABC of Twitter Sentiment Analysis. SemEval@NAACL-HLT 2016: 126-132 - 2015
- [c48]Jerzy Stefanowski:
On Properties of Undersampling Bagging and Its Extensions for Imbalanced Data. CORES 2015: 407-417 - [c47]Jerzy Stefanowski:
Adaptive Ensembles for Evolving Data Streams - Combining Block-Based and Online Solutions. NFMCP 2015: 3-16 - [c46]Mateusz Lango, Jerzy Stefanowski:
The Usefulness of Roughly Balanced Bagging for Complex and High-Dimensional Imbalanced Data. NFMCP 2015: 93-107 - 2014
- [c45]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: 61-68 - [c44]Magdalena Deckert, Jerzy Stefanowski:
RILL: Algorithm for Learning Rules from Streaming Data with Concept Drift. ISMIS 2014: 20-29 - [c43]Jerzy Stefanowski, Krystyna Napierala, Malgorzata Trzcielinska:
Local Characteristics of Minority Examples in Pre-processing of Imbalanced Data. ISMIS 2014: 123-132 - [c42]Dariusz Brzezinski, Jerzy Stefanowski:
Prequential AUC for Classifier Evaluation and Drift Detection in Evolving Data Streams. NFMCP 2014: 87-101 - [c41]Jerzy Stefanowski:
The Impact of Local Data Characteristics on Learning from Imbalanced Data. RSEISP 2014: 1-13 - 2013
- [c40]Jerzy Blaszczynski, Jerzy Stefanowski, Lukasz Idkowiak:
Extending Bagging for Imbalanced Data. CORES 2013: 269-278 - 2012
- [c39]Magdalena Deckert, Jerzy Stefanowski:
Comparing Block Ensembles for Data Streams with Concept Drift. ADBIS Workshops 2012: 69-78 - [c38]Krystyna Napierala, Jerzy Stefanowski:
Identification of Different Types of Minority Class Examples in Imbalanced Data. HAIS (2) 2012: 139-150 - [c37]Krystyna Napierala, Jerzy Stefanowski:
Modifications of Classification Strategies in Rule Set Based Bagging for Imbalanced Data. HAIS (2) 2012: 514-525 - 2011
- [c36]Tomasz Maciejewski, Jerzy Stefanowski:
Local neighbourhood extension of SMOTE for mining imbalanced data. CIDM 2011: 104-111 - [c35]Dariusz Brzezinski, Jerzy Stefanowski:
Accuracy Updated Ensemble for Data Streams with Concept Drift. HAIS (2) 2011: 155-163 - 2010
- [c34]Krystyna Napierala, Jerzy Stefanowski:
Argument Based Generalization of MODLEM Rule Induction Algorithm. RSCTC 2010: 138-147 - [c33]Jerzy Blaszczynski, Magdalena Deckert, Jerzy Stefanowski, Szymon Wilk:
Integrating Selective Pre-processing of Imbalanced Data with Ivotes Ensemble. RSCTC 2010: 148-157 - [c32]Krystyna Napierala, Jerzy Stefanowski, Szymon Wilk:
Learning from Imbalanced Data in Presence of Noisy and Borderline Examples. RSCTC 2010: 158-167 - [c31]Jerzy Blaszczynski, Roman Slowinski, Jerzy Stefanowski:
Ordinal Classification with Monotonicity Constraints by Variable Consistency Bagging. RSCTC 2010: 392-401 - 2009
- [c30]Jerzy Blaszczynski, Jerzy Stefanowski, Magdalena Zajac:
Ensembles of Abstaining Classifiers Based on Rule Sets. ISMIS 2009: 382-391 - 2008
- [c29]Jerzy Stefanowski, Szymon Wilk:
Selective Pre-processing of Imbalanced Data for Improving Classification Performance. DaWaK 2008: 283-292 - 2007
- [c28]Jerzy Stefanowski, Dawid Weiss:
Comprehensible and Accurate Cluster Labels in Text Clustering. RIAO 2007: 198-209 - [c27]Jerzy Stefanowski:
Combining Answers of Sub-classifiers in the Bagging-Feature Ensembles. RSEISP 2007: 574-583 - [c26]Salvatore Greco, Roman Slowinski, Jerzy Stefanowski:
Evaluating Importance of Conditions in the Set of Discovered Rules. RSFDGrC 2007: 314-321 - 2006
- [c25]Jerzy Stefanowski, Marcin Zienkowicz:
Classification of Polish Email Messages: Experiments with Various Data Representations. ISMIS 2006: 723-728 - 2005
- [c24]Jerzy Stefanowski, Radoslaw Z. Ziembinski:
Mining Context Based Sequential Patterns. AWIC 2005: 401-407 - [c23]Jerzy Stefanowski, Slawomir Nowaczyk:
On Using Rule Induction in Multiple Classifiers with a Combiner Aggregation Strategy. ISDA 2005: 432-437 - 2004
- [c22]Stanislaw Osinski, Jerzy Stefanowski, Dawid Weiss:
Lingo: Search Results Clustering Algorithm Based on Singular Value Decomposition. Intelligent Information Systems 2004: 359-368 - [c21]Jerzy W. Grzymala-Busse, Jerzy Stefanowski, Szymon Wilk:
A Comparison of Two Approaches to Data Mining from Imbalanced Data. KES 2004: 757-763 - [c20]Jerzy Stefanowski:
The Bagging and n2-Classifiers Based on Rules Induced by MODLEM. Rough Sets and Current Trends in Computing 2004: 488-497 - 2003
- [c19]Jerzy Stefanowski, Dawid Weiss:
Carrot and Language Properties in Web Search Results Clustering. AWIC 2003: 240-249 - [c18]Dawid Weiss, Jerzy Stefanowski:
Web Search Results Clustering in Polish: Experimental Evaluation of Carrot. IIS 2003: 209-218 - [c17]Jerzy Stefanowski, Marcin Zurawski:
Incremental Rule Induction for Multicriteria and Multiattribute Classification. IIS 2003: 311-319 - 2002
- [c16]Jerzy Stefanowski:
Bagging and Induction of Decision Rules. Intelligent Information Systems 2002: 121-130 - [c15]Salvatore Greco, Roman Slowinski, Jerzy Stefanowski:
Mining Association Rules in Preference-Ordered Data. ISMIS 2002: 442-450 - [c14]Salvatore Greco, Benedetto Matarazzo, Roman Slowinski, Jerzy Stefanowski:
Importance and Interaction of Conditions in Decision Rules. Rough Sets and Current Trends in Computing 2002: 255-262 - [c13]Jerzy Stefanowski, Alexis Tsoukiàs:
Induction of Decision Rules and Classification in the Valued Tolerance Approach. Rough Sets and Current Trends in Computing 2002: 271-278 - 2000
- [c12]Salvatore Greco, Benedetto Matarazzo, Roman Slowinski, Jerzy Stefanowski:
Variable Consistency Model of Dominance-Based Rough Sets Approach. Rough Sets and Current Trends in Computing 2000: 170-181 - [c11]Jerzy Stefanowski, Alexis Tsoukiàs:
Valued Tolerance and Decision Rules. Rough Sets and Current Trends in Computing 2000: 212-219 - [c10]Salvatore Greco, Benedetto Matarazzo, Roman Slowinski, Jerzy Stefanowski:
An Algorithm for Induction of Decision Rules Consistent with the Dominance Principle. Rough Sets and Current Trends in Computing 2000: 304-313 - 1999
- [c9]Jerzy Stefanowski, Alexis Tsoukiàs:
On the Extension of Rough Sets under Incomplete Information. RSFDGrC 1999: 73-81 - 1998
- [c8]Jacek Jelonek, Jerzy Stefanowski:
Experiments on Solving Multiclass Learning Problems by n2-classifier. ECML 1998: 172-177 - [c7]Jerzy Stefanowski:
Handling Continuous Attributes in Discovery of Strong Decision Rules. Rough Sets and Current Trends in Computing 1998: 394-401 - [c6]Bartlomiej Predki, Roman Slowinski, Jerzy Stefanowski, Robert Susmaga, Szymon Wilk:
ROSE - Software Implementation of the Rough Set Theory. Rough Sets and Current Trends in Computing 1998: 605-608 - 1997
- [c5]Jerzy Stefanowski, Krzysztof Slowinski:
Rough Set Theory and Rule Induction Techniques for Discovery of Attribute Dependencies in Medical Information Systems. PKDD 1997: 36-46 - 1993
- [c4]Jerzy Stefanowski, Daniel Vanderpooten:
A General Two-Stage Approach to Inducing Rules from Examples. RSKD 1993: 317-325 - [c3]Roman Slowinski, Jerzy Stefanowski:
Handling Various Types of Uncertainty in the Rough Set Approach. RSKD 1993: 366-376 - [c2]Jacek Jelonek, Krzysztof Krawiec, Roman Slowinski, Jerzy Stefanowski, Janusz Szymas:
Neural Networks and Rough Sets - Comparison and Combination for Classification of Histological Pictures. RSKD 1993: 426-433 - 1992
- [c1]Jerzy Stefanowski, Roman Slowinski, Ryszard Nowicki:
The Rough Sets Approach to Knowledge Analysis for Classification Support in Technical Diagnostics of Mechanical Objects. IEA/AIE 1992: 556-565
Parts in Books or Collections
- 2018
- [p5]Jerzy Blaszczynski, Jerzy Stefanowski:
Improving Bagging Ensembles for Class Imbalanced Data by Active Learning. Advances in Feature Selection for Data and Pattern Recognition 2018: 25-52 - 2016
- [p4]Jerzy Stefanowski:
Dealing with Data Difficulty Factors While Learning from Imbalanced Data. Challenges in Computational Statistics and Data Mining 2016: 333-363 - 1992
- [p3]Ryszard Nowicki, Roman Slowinski, Jerzy Stefanowski:
Analysis of Diagnostic Symptoms in Vibroacoustic Diagnostics by Means of the Rough Sets Theory. Intelligent Decision Support 1992: 33-48 - [p2]Ewa Krusinska, Ankica Babic, Roman Slowinski, Jerzy Stefanowski:
Comparison of the Rough Sets Approach and Probabilistic Data Analysis Techniques on a Common Set of Medical Data. Intelligent Decision Support 1992: 251-265 - [p1]Roman Slowinski, Jerzy Stefanowski:
'Roughdas' and 'Roughclass' Software Implementations of the Rough Sets Approach. Intelligent Decision Support 1992: 445-456
Editorship
- 2019
- [e3]Mar Marcos, Jose M. Juarez, Richard Lenz, Grzegorz J. Nalepa, Slawomir Nowaczyk, Mor Peleg, Jerzy Stefanowski, Gregor Stiglic:
Artificial Intelligence in Medicine: Knowledge Representation and Transparent and Explainable Systems - AIME 2019 International Workshops, KR4HC/ProHealth and TEAAM, Poznan, Poland, June 26-29, 2019, Revised Selected Papers. Lecture Notes in Computer Science 11979, Springer 2019, ISBN 978-3-030-37445-7 [contents] - 2017
- [e2]Yasemin Altun, Kamalika Das, Taneli Mielikäinen, Donato Malerba, Jerzy Stefanowski, Jesse Read, Marinka Zitnik, Michelangelo Ceci, Saso Dzeroski:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part III. Lecture Notes in Computer Science 10536, Springer 2017, ISBN 978-3-319-71272-7 [contents] - 2007
- [e1]Aijun An, Jerzy Stefanowski, Sheela Ramanna, Cory J. Butz, Witold Pedrycz, Guoyin Wang:
Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, 11th International Conference, RSFDGrC 2007, Toronto, Canada, May 14-16, 2007, Proceedings. Lecture Notes in Computer Science 4482, Springer 2007, ISBN 978-3-540-72529-9 [contents]
Reference Works
- 2017
- [r1]Jerzy Stefanowski, Dariusz Brzezinski:
Stream Classification. Encyclopedia of Machine Learning and Data Mining 2017: 1191-1199
Informal and Other Publications
- 2024
- [i11]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 abs/2403.13940 (2024) - [i10]Patryk Wielopolski, Oleksii Furman, Jerzy Stefanowski, Maciej Zieba:
Probabilistically Plausible Counterfactual Explanations with Normalizing Flows. CoRR abs/2405.17640 (2024) - [i9]Patryk Wielopolski, Oleksii Furman, Jerzy Stefanowski, Maciej Zieba:
Unifying Perspectives: Plausible Counterfactual Explanations on Global, Group-wise, and Local Levels. CoRR abs/2405.17642 (2024) - [i8]Jacek Karolczak, Jerzy Stefanowski:
A-PETE: Adaptive Prototype Explanations of Tree Ensembles. CoRR abs/2405.21036 (2024) - [i7]Ignacy Stepka, Mateusz Lango, Jerzy Stefanowski:
Counterfactual Explanations with Probabilistic Guarantees on their Robustness to Model Change. CoRR abs/2408.04842 (2024) - 2023
- [i6]Riccardo Albertoni, Sara Colantonio, Piotr Skrzypczynski, Jerzy Stefanowski:
Reproducibility of Machine Learning: Terminology, Recommendations and Open Issues. CoRR abs/2302.12691 (2023) - [i5]Damian Horna, Mateusz Lango, Jerzy Stefanowski:
Deep Similarity Learning Loss Functions in Data Transformation for Class Imbalance. CoRR abs/2312.10556 (2023) - [i4]Jakub Raczynski, Mateusz Lango, Jerzy Stefanowski:
The Problem of Coherence in Natural Language Explanations of Recommendations. CoRR abs/2312.11356 (2023) - 2022
- [i3]Witold Andrzejewski, Jedrzej Potoniec, Maciej Drozdowski, Jerzy Stefanowski, Robert Wrembel, Pawel Stapf:
Quality versus speed in energy demand prediction for district heating systems. CoRR abs/2205.07863 (2022) - [i2]Agnieszka Lipska, Jerzy Stefanowski:
The Influence of Multiple Classes on Learning Online Classifiers from Imbalanced and Concept Drifting Data Streams. CoRR abs/2210.08359 (2022) - 2017
- [i1]Dariusz Brzezinski, Jerzy Stefanowski, Robert Susmaga, Izabela Szczech:
Visual-Based Analysis of Classification Measures with Applications to Imbalanced Data. CoRR abs/1704.07122 (2017)
Coauthor Index
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Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
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OpenAlex data
Load additional information about publications from 
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last updated on 2024-10-31 20:13 CET by the dblp team
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