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ORCIDPawel Ksieniewicz
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2020 – today
- 2024
[j24]Joanna Komorniczak
, Tobiasz Puslecki, Pawel Ksieniewicz, Krzysztof Walkowiak:
Certainty-Based Neural Network Architecture Selection Framework for TinyML Systems. IEEE Access 12: 155632-155643 (2024)- [j23]Joanna Komorniczak, Pawel Ksieniewicz:
torchosr - A PyTorch extension package for Open Set Recognition models evaluation in Python. Neurocomputing 566: 127047 (2024) - [j22]Joanna Komorniczak, Pawel Ksieniewicz:
Distance profile layer for binary classification and density estimation. Neurocomputing 579: 127436 (2024) - [j21]Rafal Kozik, Gracjan Katek, Marta Gackowska, Sebastian Kula, Joanna Komorniczak, Pawel Ksieniewicz, Aleksandra Pawlicka, Marek Pawlicki, Michal Choras:
Towards explainable fake news detection and automated content credibility assessment: Polish internet and digital media use-case. Neurocomputing 608: 128450 (2024) - [j20]Joanna Komorniczak, Pawel Ksieniewicz:
On metafeatures' ability of implicit concept identification. Mach. Learn. 113(10): 7931-7966 (2024) - [c38]Gracjan Katek, Marta Gackowska, Joanna Komorniczak, Pawel Ksieniewicz, Rafal Kozik, Marek Pawlicki, Michal Choras:
Involving Society to Protect Society from Fake News and Disinformation: Crowdsourced Datasets and Text Reliability Assessment. ACIIDS (2) 2024: 384-395 - [i10]Joanna Komorniczak, Pawel Ksieniewicz:
Taking Class Imbalance Into Account in Open Set Recognition Evaluation. CoRR abs/2402.06331 (2024) - [i9]Joanna Komorniczak, Pawel Ksieniewicz:
Unsupervised Concept Drift Detection based on Parallel Activations of Neural Network. CoRR abs/2404.07776 (2024) - [i8]Weronika Borek-Marciniec, Pawel Zyblewski, Jakub Klikowski, Pawel Ksieniewicz:
WarCov - Large multilabel and multimodal dataset from social platform. CoRR abs/2406.10255 (2024) - [i7]Pawel Zyblewski, Jakub Klikowski, Weronika Borek-Marciniec, Pawel Ksieniewicz:
Employing Sentence Space Embedding for Classification of Data Stream from Fake News Domain. CoRR abs/2407.10807 (2024) - 2023
- [j19]Pawel Ksieniewicz:
Processing data stream with chunk-similarity model selection. Appl. Intell. 53(7): 7931-7956 (2023) - [j18]Weronika Borek-Marciniec, Pawel Ksieniewicz:
Neural network architecture with intermediate distribution-driven layer for classification of multidimensional data with low class separability. Appl. Intell. 53(21): 26050-26066 (2023) - [j17]Pawel Ksieniewicz, Pawel Zyblewski, Weronika Borek-Marciniec, Rafal Kozik, Michal Choras, Michal Wozniak:
Alphabet Flatting as a variant of n-gram feature extraction method in ensemble classification of fake news. Eng. Appl. Artif. Intell. 120: 105882 (2023) - [j16]Joanna Komorniczak, Pawel Ksieniewicz:
problexity - An open-source Python library for supervised learning problem complexity assessment. Neurocomputing 521: 126-136 (2023) - [j15]Joanna Komorniczak, Pawel Ksieniewicz:
Complexity-based drift detection for nonstationary data streams. Neurocomputing 552: 126554 (2023) - [j14]Michal Wozniak, Pawel Zyblewski, Pawel Ksieniewicz:
Active Weighted Aging Ensemble for drifted data stream classification. Inf. Sci. 630: 286-304 (2023) - [c37]Rafal Kozik, Joanna Komorniczak, Pawel Ksieniewicz, Aleksandra Pawlicka, Marek Pawlicki, Michal Choras:
SWAROG Project Approach to Fake News Detection Problem. CISIS-ICEUTE 2023: 79-88 - [c36]Weronika Borek-Marciniec, Pawel Ksieniewicz:
Hollow n-grams Vectorizer for Natural Language Processing Problems. CORES/IP&C 2023: 15-22 - [c35]Karol Wojtachnia, Joanna Komorniczak, Pawel Ksieniewicz:
Incremental Extreme Learning Machine for Binary Data Stream Classification. CORES/IP&C 2023: 35-44 - [c34]Joanna Komorniczak, Pawel Ksieniewicz, Michal Wozniak:
Analysis of the Possibility to Employ Relationship Between the Problem Complexity and the Classification Quality as Model Optimization Proxy. CORES/IP&C 2023: 71-82 - [e1]Robert Burduk, Michal Choras, Rafal Kozik, Pawel Ksieniewicz, Tomasz Marciniak, Pawel Trajdos:
Progress on Pattern Classification, Image Processing and Communications - Proceedings of the CORES and IP&C Conferences 2023, Wrocław, Poland. Lecture Notes in Networks and Systems 766, Springer 2023, ISBN 978-3-031-41629-3 [contents] - [i6]Joanna Komorniczak, Pawel Ksieniewicz:
torchosr - a PyTorch extension package for Open Set Recognition models evaluation in Python. CoRR abs/2305.09646 (2023) - 2022
- [j13]Szymon Wojciechowski, Róza Goscien, Pawel Ksieniewicz, Krzysztof Walkowiak:
Hybrid Regression Model for Link Dimensioning in Spectrally-Spatially Flexible Optical Networks. IEEE Access 10: 53810-53821 (2022) - [j12]Pawel Ksieniewicz, Pawel Zyblewski:
Stream-learn - open-source Python library for difficult data stream batch analysis. Neurocomputing 478: 11-21 (2022) - [j11]Joanna Komorniczak, Pawel Zyblewski, Pawel Ksieniewicz:
Statistical Drift Detection Ensemble for batch processing of data streams. Knowl. Based Syst. 252: 109380 (2022) - [j10]Róza Goscien, Pawel Ksieniewicz:
Efficient dynamic routing in Spectrally-Spatially Flexible Optical Networks based on traffic categorization and supervised learning methods. Opt. Switch. Netw. 43: 100650 (2022) - [c33]Jedrzej Kozal, Michal Les, Pawel Zyblewski, Pawel Ksieniewicz, Michal Wozniak:
Feature Integration Strategies for Multilingual Fake News Classification. IEEE Big Data 2022: 5049-5058 - [c32]Joanna Komorniczak, Pawel Ksieniewicz:
Data stream generation through real concept's interpolation. ESANN 2022 - [c31]Weronika Borek, Pawel Ksieniewicz:
Inductive Parallel Learning for Multiple Classification Problems. IJCNN 2022: 1-8 - [c30]Joanna Komorniczak, Pawel Zyblewski, Pawel Ksieniewicz:
Imbalanced Data Stream Classification Assisted by Prior Probability Estimation. IJCNN 2022: 1-8 - [c29]Joanna Komorniczak, Pawel Ksieniewicz, Michal Wozniak:
Data complexity and classification accuracy correlation in oversampling algorithms. LIDTA 2022: 175-186 - [i5]Jedrzej Kozal, Michal Les, Pawel Zyblewski, Pawel Ksieniewicz, Michal Wozniak:
Lifelong Learning Natural Language Processing Approach for Multilingual Data Classification. CoRR abs/2206.11867 (2022) - [i4]Joanna Komorniczak, Pawel Ksieniewicz:
problexity - an open-source Python library for binary classification problem complexity assessment. CoRR abs/2207.06709 (2022) - 2021
- [j9]Michal Choras, Konstantinos P. Demestichas, Agata Gielczyk, Álvaro Herrero, Pawel Ksieniewicz, Konstantina Remoundou, Daniel Urda, Michal Wozniak:
Advanced Machine Learning techniques for fake news (online disinformation) detection: A systematic mapping study. Appl. Soft Comput. 101: 107050 (2021) - [j8]Katarzyna Stapor, Pawel Ksieniewicz, Salvador García, Michal Wozniak:
How to design the fair experimental classifier evaluation. Appl. Soft Comput. 104: 107219 (2021) - [j7]Pawel Ksieniewicz:
The prior probability in the batch classification of imbalanced data streams. Neurocomputing 452: 309-316 (2021) - [j6]Pawel Ksieniewicz, Pawel Zyblewski, Robert Burduk:
Fusion of linear base classifiers in geometric space. Knowl. Based Syst. 227: 107231 (2021) - [c28]Dominika Sulot, Pawel Zyblewski, Pawel Ksieniewicz:
Analysis of Variance Application in the Construction of Classifier Ensemble Based on Optimal Feature Subset for the Task of Supporting Glaucoma Diagnosis. ICCS (3) 2021: 109-117 - [c27]Joanna Komorniczak, Pawel Zyblewski, Pawel Ksieniewicz:
Prior Probability Estimation in Dynamically Imbalanced Data Streams. IJCNN 2021: 1-7 - [i3]Michal Choras, Konstantinos P. Demestichas, Agata Gielczyk, Álvaro Herrero, Pawel Ksieniewicz, Konstantina Remoundou, Daniel Urda, Michal Wozniak:
Advanced Machine Learning Techniques for Fake News (Online Disinformation) Detection: A Systematic Mapping Study. CoRR abs/2101.01142 (2021) - [i2]Michal Wozniak, Pawel Zyblewski, Pawel Ksieniewicz:
Active Weighted Aging Ensemble for Drifted Data Stream Classification. CoRR abs/2112.10150 (2021) - 2020
- [j5]Weronika Wegier, Pawel Ksieniewicz:
Application of Imbalanced Data Classification Quality Metrics as Weighting Methods of the Ensemble Data Stream Classification Algorithms. Entropy 22(8): 849 (2020) - [c26]Pawel Zyblewski, Pawel Ksieniewicz, Michal Wozniak:
Combination of Active and Random Labeling Strategy in the Non-stationary Data Stream Classification. ICAISC (1) 2020: 576-585 - [c25]Pawel Ksieniewicz:
Standard Decision Boundary in a Support-Domain of Fuzzy Classifier Prediction for the Task of Imbalanced Data Classification. ICCS (4) 2020: 103-116 - [c24]Pawel Ksieniewicz, Robert Burduk:
Clustering and Weighted Scoring in Geometric Space Support Vector Machine Ensemble for Highly Imbalanced Data Classification. ICCS (4) 2020: 128-140 - [c23]Pawel Ksieniewicz, Róza Goscien, Miroslaw Klinkowski, Krzysztof Walkowiak:
Pattern Recognition Model to Aid the Optimization of Dynamic Spectrally-Spatially Flexible Optical Networks. ICCS (4) 2020: 211-224 - [c22]Sebastian Kula, Michal Choras, Rafal Kozik, Pawel Ksieniewicz, Michal Wozniak:
Sentiment Analysis for Fake News Detection by Means of Neural Networks. ICCS (4) 2020: 653-666 - [c21]Pawel Ksieniewicz, Pawel Zyblewski, Michal Choras, Rafal Kozik, Agata Gielczyk, Michal Wozniak:
Fake News Detection from Data Streams. IJCNN 2020: 1-8 - [i1]Pawel Ksieniewicz, Pawel Zyblewski:
stream-learn - open-source Python library for difficult data stream batch analysis. CoRR abs/2001.11077 (2020)
2010 – 2019
- 2019
- [j4]Pawel Ksieniewicz, Michal Wozniak, Boguslaw Cyganek, Andrzej Kasprzak, Krzysztof Walkowiak:
Data stream classification using active learned neural networks. Neurocomputing 353: 74-82 (2019) - [c20]Pawel Ksieniewicz:
Combining Random Subspace Approach with smote Oversampling for Imbalanced Data Classification. HAIS 2019: 660-673 - [c19]Pawel Zyblewski, Pawel Ksieniewicz, Michal Wozniak:
Classifier Selection for Highly Imbalanced Data Streams with Minority Driven Ensemble. ICAISC (1) 2019: 626-635 - [c18]Bogdan Gulowaty, Pawel Ksieniewicz:
SMOTE Algorithm Variations in Balancing Data Streams. IDEAL (2) 2019: 305-312 - [c17]Jedrzej Kozal, Pawel Ksieniewicz:
Imbalance Reduction Techniques Applied to ECG Classification Problem. IDEAL (2) 2019: 323-331 - [c16]Pawel Ksieniewicz, Michal Choras, Rafal Kozik, Michal Wozniak:
Machine Learning Methods for Fake News Classification. IDEAL (2) 2019: 332-339 - [c15]Jakub Klikowski, Pawel Ksieniewicz, Michal Wozniak:
A Genetic-Based Ensemble Learning Applied to Imbalanced Data Classification. IDEAL (2) 2019: 340-352 - 2018
- [j3]Pawel Ksieniewicz, Bartosz Krawczyk, Michal Wozniak:
Ensemble of Extreme Learning Machines with trained classifier combination and statistical features for hyperspectral data. Neurocomputing 271: 28-37 (2018) - [c14]Andrzej Lapinski, Bartosz Krawczyk, Pawel Ksieniewicz, Michal Wozniak:
An Empirical Insight Into Concept Drift Detectors Ensemble Strategies. CEC 2018: 1-8 - [c13]Pawel Ksieniewicz, Michal Wozniak:
Imbalanced Data Classification Based on Feature Selection Techniques. IDEAL (2) 2018: 296-303 - [c12]Pawel Ksieniewicz:
Combined Classifier Based on Quantized Subspace Class Distribution. IDEAL (1) 2018: 761-772 - [c11]Pawel Ksieniewicz:
Undersampled Majority Class Ensemble for highly imbalanced binary classification. LIDTA@ECML/PKDD 2018: 82-94 - 2017
- [j2]Pawel Ksieniewicz, Manuel Graña, Michal Wozniak:
Paired feature multilayer ensemble - concept and evaluation of a classifier. J. Intell. Fuzzy Syst. 32(2): 1427-1436 (2017) - [c10]Pawel Ksieniewicz, Michal Wozniak:
Dealing with the task of imbalanced, multidimensional data classification using ensembles of exposers. LIDTA@PKDD/ECML 2017: 164-175 - 2016
- [c9]Michal Wozniak, Pawel Ksieniewicz, Boguslaw Cyganek, Krzysztof Walkowiak:
Ensembles of Heterogeneous Concept Drift Detectors - Experimental Study. CISIM 2016: 538-549 - [c8]Pawel Ksieniewicz, Bartosz Krawczyk, Michal Wozniak:
Ensemble of One-Dimensional Classifiers for Hyperspectral Image Analysis. DMBD 2016: 513-520 - [c7]Michal Wozniak, Boguslaw Cyganek, Andrzej Kasprzak, Pawel Ksieniewicz, Krzysztof Walkowiak:
Active Learning Classifier for Streaming Data. HAIS 2016: 186-197 - [c6]Michal Wozniak, Pawel Ksieniewicz, Boguslaw Cyganek, Andrzej Kasprzak, Krzysztof Walkowiak:
Active Learning Classification of Drifted Streaming Data. ICCS 2016: 1724-1733 - [c5]Michal Wozniak, Pawel Ksieniewicz, Andrzej Kasprzak, Karol Puchala, Przemyslaw Ryba:
A First Attempt to Construct Effective Concept Drift Detector Ensembles. IP&C 2016: 27-34 - 2015
- [j1]Pawel Ksieniewicz, Dariusz Jankowski, Borja Ayerdi, Konrad Jackowski, Manuel Graña, Michal Wozniak:
A novel hyperspectral segmentation algorithm - concept and evaluation. Log. J. IGPL 23(1): 105-120 (2015) - [c4]Pawel Ksieniewicz, Michal Wozniak:
Artificial Photoreceptors for Ensemble Classification of Hyperspectral Images. CORES 2015: 471-479 - [c3]Pawel Ksieniewicz, Manuel Graña, Michal Wozniak:
Blurred Labeling Segmentation Algorithm for Hyperspectral Images. ICCCI (2) 2015: 578-587 - 2014
- [c2]Bartosz Krawczyk, Pawel Ksieniewicz, Michal Wozniak:
Hyperspectral Image Analysis Based on Color Channels and Ensemble Classifier. HAIS 2014: 274-284 - [c1]Bartosz Krawczyk, Pawel Ksieniewicz, Michal Wozniak:
Hyperspectral Image Analysis Based on Quad Tree Decomposition. SOCO-CISIS-ICEUTE 2014: 105-113
Coauthor Index
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