Designing Cost-Sensitive Ensemble - Genetic Approach. - Bartosz Krawczyk; Michal Wozniak 001 (IP&C, 2011)

Privacy Preserving Models of k-NN Algorithm. - Bartosz Krawczyk; Michal Wozniak 001 (Computer Recognition Systems 4, 2011)

Diversity in Ensembles for One-Class Classification. - Bartosz Krawczyk (ADBIS Workshops, 2012)

Breast thermogram analysis using a cost-sensitive multiple classifier system. - Bartosz Krawczyk; Gerald Schaefer; Michal Wozniak 001 (BHI, 2012)

Experiments on distance measures for combining one-class classifiers. - Bartosz Krawczyk; Michal Wozniak 001 (FedCSIS, 2012)

Combining Diverse One-Class Classifiers. - Bartosz Krawczyk; Michal Wozniak 001 (HAIS (2), 2012)

Adaptive Splitting and Selection Algorithm for Classification of Breast Cytology Images. - Bartosz Krawczyk; Pawel Filipczuk; Michal Wozniak 001 (ICCCI (1), 2012)

Oversampling Methods for Classification of Imbalanced Breast Cancer Malignancy Data. - Bartosz Krawczyk; Lukasz Jelen; Adam Krzyzak; Thomas Fevens (ICCVG, 2012)

Effective multiple classifier systems for breast thermogram analysis. - Bartosz Krawczyk; Gerald Schaefer (ICPR, 2012)

Cost-Sensitive Splitting and Selection Method for Medical Decision Support System. - Konrad Jackowski; Bartosz Krawczyk; Michal Wozniak 001 (IDEAL, 2012)

Analysis of Diversity Assurance Methods for Combined Classifiers. - Bartosz Krawczyk; Michal Wozniak 001 (IP&C, 2012)

Combined Classifiers with Neural Fuser for Spam Detection. - Marcin Zmyslony; Bartosz Krawczyk; Michal Wozniak 001 (CISIS/ICEUTE/SOCO Special Sessions, 2012)

Combined classifier based on feature space partitioning. - Michal Wozniak 001; Bartosz Krawczyk (Int. J. Appl. Math. Comput. Sci., 2012)

Adaptive Splitting and Selection Method for Noninvasive Recognition of Liver Fibrosis Stage. - Bartosz Krawczyk; Michal Wozniak 001; Tomasz Orczyk; Piotr Porwik (ACIIDS (2), 2013)

An Analysis of Properties of Malignant Cases for Imbalanced Breast Thermogram Feature Classification. - Bartosz Krawczyk; Gerald Schaefer (ACPR, 2013)

HEp-2 Cell Classification Using Multi-dimensional Local Binary Patterns and Ensemble Classification. - Gerald Schaefer; Niraj P. Doshi; Bartosz Krawczyk (ACPR, 2013)

Melanoma Classification Using Dermoscopy Imaging and Ensemble Learning. - Gerald Schaefer; Bartosz Krawczyk; M. Emre Celebi 001; Hitoshi Iyatomi (ACPR, 2013)

Breast Cancer Identification Based on Thermal Analysis and a Clustering and Selection Classification Ensemble. - Bartosz Krawczyk; Gerald Schaefer; Shao Ying Zhu (Brain and Health Informatics, 2013)

Accuracy and diversity in classifier selection for one-class classification ensembles. - Bartosz Krawczyk; Michal Wozniak 001 (CIEL, 2013)

On diversity measures for fuzzy one-class classifier ensembles. - Bartosz Krawczyk; Michal Wozniak 001 (CIEL, 2013)

Combining one-class classifiers for imbalanced classification of breast thermogram features. - Bartosz Krawczyk; Gerald Schaefer; Michal Wozniak 001 (CIMI, 2013)

Incremental Learning and Forgetting in One-Class Classifiers for Data Streams. - Bartosz Krawczyk; Michal Wozniak 001 (CORES, 2013)

Cost Sensitive Hierarchical Classifiers for Non-invasive Recognition of Liver Fibrosis Stage. - Bartosz Krawczyk; Michal Wozniak 001; Tomasz Orczyk; Piotr Porwik (CORES, 2013)

A pruned ensemble classifier for effective breast thermogram analysis. - Bartosz Krawczyk; Gerald Schaefer (EMBC, 2013)

Scleroderma capillary pattern identification using texture descriptors and ensemble classification. - Gerald Schaefer; Bartosz Krawczyk; Niraj P. Doshi; Arcangelo Merla (EMBC, 2013)

Combining One-Class Support Vector Machines for Microarray Classification. - Bartosz Krawczyk (FedCSIS, 2013)

Distributed Privacy-Preserving Minimal Distance Classification. - Bartosz Krawczyk; Michal Wozniak 001 (HAIS, 2013)

Pruning One-Class Classifier Ensembles by Combining Sphere Intersection and Consistency Measures. - Bartosz Krawczyk; Michal Wozniak 001 (ICAISC (1), 2013)

Improved LBP texture classification using ensemble learning. - Gerald Schaefer; Bartosz Krawczyk; Niraj P. Doshi (ICME, 2013)

An improved ensemble approach for imbalanced classification problems. - Bartosz Krawczyk; Gerald Schaefer (SACI, 2013)

A cost-sensitive ensemble classifier for breast cancer classification. - Bartosz Krawczyk; Gerald Schaefer; Michal Wozniak 001 (SACI, 2013)

Application of Adaptive Splitting and Selection Classifier to the Spam Filtering Problem. - Konrad Jackowski; Bartosz Krawczyk; Michal Wozniak 001 (Cybern. Syst., 2013)

On optimal settings of classification tree ensembles for medical decision support. - Mateusz Budnik; Bartosz Krawczyk (Health Informatics J., 2013)

Classifier ensemble for an effective cytological image analysis. - Pawel Filipczuk; Bartosz Krawczyk; Michal Wozniak 001 (Pattern Recognit. Lett., 2013)

E-medical diagnosis support system for non-invasive liver fibrosis recognition. - Tomasz Orczyk; Piotr Porwik; Bartosz Krawczyk; Michal Wozniak 001; Joanna Musialik; Barbara Blonska-Fajfrowska (Stud. Inform. Univ., 2013)

Optimization Algorithms for One-Class Classification Ensemble Pruning. - Bartosz Krawczyk; Michal Wozniak 001 (ACIIDS (2), 2014)

Melanoma Classification Based on Ensemble Classification of Dermoscopy Image Features. - Gerald Schaefer; Bartosz Krawczyk; M. Emre Celebi 001; Hitoshi Iyatomi; Aboul Ella Hassanien (AMLTA, 2014)

A first attempt on evolutionary prototype reduction for nearest neighbor one-class classification. - Bartosz Krawczyk; Isaac Triguero; Salvador García 001; Michal Wozniak 001; Francisco Herrera (IEEE Congress on Evolutionary Computation, 2014)

Cost-sensitive texture classification. - Gerald Schaefer; Bartosz Krawczyk; Niraj P. Doshi; Tomoharu Nakashima (IEEE Congress on Evolutionary Computation, 2014)

Adaptive Splitting and Selection ensemble for breast cancer malignancy grading. - Bartosz Krawczyk; Lukasz Jelen; Michal Wozniak 001 (CICARE, 2014)

Weighted one-class classification for different types of minority class examples in imbalanced data. - Bartosz Krawczyk; Michal Wozniak 001; Francisco Herrera (CIDM, 2014)

Experiments on simultaneous combination rule training and ensemble pruning algorithm. - Bartosz Krawczyk; Michal Wozniak 001 (CIEL, 2014)

Designing a compact Genetic fuzzy rule-based system for one-class classification. - Pedro Villar; Bartosz Krawczyk; Ana M. Sánchez; Rosana Montes; Francisco Herrera (FUZZ-IEEE, 2014)

Hyperspectral Image Analysis Based on Color Channels and Ensemble Classifier. - Bartosz Krawczyk; Pawel Ksieniewicz; Michal Wozniak 001 (HAIS, 2014)

Clustering-Based Ensemble of One-Class Classifiers for Hyperspectral Image Segmentation. - Bartosz Krawczyk; Michal Wozniak 001; Boguslaw Cyganek (HAIS, 2014)

One-Class Classification Decomposition for Imbalanced Classification of Breast Cancer Malignancy Data. - Bartosz Krawczyk; Lukasz Jelen; Adam Krzyzak; Thomas Fevens (ICAISC (1), 2014)

Weighted One-Class Classifier Ensemble Based on Fuzzy Feature Space Partitioning. - Bartosz Krawczyk; Michal Wozniak 001; Boguslaw Cyganek (ICPR, 2014)

Hypertension Type Classification Using Hierarchical Ensemble of One-Class Classifiers for Imbalanced Data. - Bartosz Krawczyk; Michal Wozniak 001 (ICT Innovations, 2014)

Handling Label Noise in Microarray Classification with One-Class Classifier Ensemble. - Bartosz Krawczyk; Michal Wozniak 001 (ICT Innovations, 2014)

New untrained aggregation methods for classifier combination. - Bartosz Krawczyk; Michal Wozniak 001 (IJCNN, 2014)

Untrained Method for Ensemble Pruning and Weighted Combination. - Bartosz Krawczyk; Michal Wozniak 001 (ISNN, 2014)

One-Class Classification Ensemble with Dynamic Classifier Selection. - Bartosz Krawczyk; Michal Wozniak 001 (ISNN, 2014)

Determination of changes in plasma structure during extracorporeal circulation - studies by ATR-FTIR spectroscopy and machine learning methods. - Sylwia Olsztynska-Janus; Barbara Kmiecik; Bartosz Krawczyk; Malgorzata Komorowska (IWBBIO, 2014)

Hyperspectral Image Analysis Based on Quad Tree Decomposition. - Bartosz Krawczyk; Pawel Ksieniewicz; Michal Wozniak 001 (SOCO-CISIS-ICEUTE, 2014)

Evolutionary Cost-Sensitive Ensemble for Malware Detection. - Bartosz Krawczyk; Michal Wozniak 001 (SOCO-CISIS-ICEUTE, 2014)

Recent Advances in Applied Computational Intelligence. - Bartosz Krawczyk; Urszula Markowska-Kaczmar; Halina Kwasnicka (Appl. Artif. Intell., 2014)

Influence of Distance Measures on the Effectiveness of One-Class Classification Ensembles. - Bartosz Krawczyk; Michal Wozniak 001 (Appl. Artif. Intell., 2014)

A hybrid classifier committee for analysing asymmetry features in breast thermograms. - Bartosz Krawczyk; Gerald Schaefer (Appl. Soft Comput., 2014)

Cost-sensitive decision tree ensembles for effective imbalanced classification. - Bartosz Krawczyk; Michal Wozniak 001; Gerald Schaefer (Appl. Soft Comput., 2014)

Cytological image analysis with firefly nuclei detection and hybrid one-class classification decomposition. - Bartosz Krawczyk; Pawel Filipczuk (Eng. Appl. Artif. Intell., 2014)

Improved Adaptive Splitting and Selection: the Hybrid Training Method of a Classifier Based on a Feature Space Partitioning. - Konrad Jackowski; Bartosz Krawczyk; Michal Wozniak 001 (Int. J. Neural Syst., 2014)

Diversity measures for one-class classifier ensembles. - Bartosz Krawczyk; Michal Wozniak 001 (Neurocomputing, 2014)

Clustering-based ensembles for one-class classification. - Bartosz Krawczyk; Michal Wozniak 001; Boguslaw Cyganek (Inf. Sci., 2014)

An ensemble classification approach for melanoma diagnosis. - Gerald Schaefer; Bartosz Krawczyk; M. Emre Celebi 001; Hitoshi Iyatomi (Memetic Comput., 2014)

Breast Thermogram Analysis Using Classifier Ensembles and Image Symmetry Features. - Bartosz Krawczyk; Gerald Schaefer (IEEE Syst. J., 2014)

Data Classification with Ensembles of One-Class Support Vector Machines and Sparse Nonnegative Matrix Factorization. - Boguslaw Cyganek; Bartosz Krawczyk (ACIIDS (1), 2015)

Pruning Ensembles of One-Class Classifiers with X-means Clustering. - Bartosz Krawczyk; Michal Wozniak 001 (ACIIDS (1), 2015)

Pruning Ensembles with Cost Constraints. - Bartosz Krawczyk; Michal Wozniak 001 (ACIIDS (1), 2015)

Combining One-vs-One Decomposition and Ensemble Learning for Multi-class Imbalanced Data. - Bartosz Krawczyk (CORES, 2015)

Reacting to different types of concept drift with adaptive and incremental one-class classifiers. - Bartosz Krawczyk; Michal Wozniak 001 (CYBCONF, 2015)

Combining nearest neighbour classifiers based on small subsamples for big data analytics. - Bartosz Krawczyk; Michal Wozniak 001 (CYBCONF, 2015)

Wagging for Combining Weighted One-class Support Vector Machines. - Bartosz Krawczyk; Michal Wozniak 001 (ICCS, 2015)

Cost-Sensitive Neural Network with ROC-Based Moving Threshold for Imbalanced Classification. - Bartosz Krawczyk; Michal Wozniak 001 (IDEAL, 2015)

Effective Imbalanced Classification of Breast Thermogram Features. - Bartosz Krawczyk; Gerald Schaefer (PReMI, 2015)

Weighted Naïve Bayes Classifier with Forgetting for Drifting Data Streams. - Bartosz Krawczyk; Michal Wozniak 001 (SMC, 2015)

Incremental One-Class Bagging for Streaming and Evolving Big Data. - Bartosz Krawczyk; Michal Wozniak 001 (TrustCom/BigDataSE/ISPA (2), 2015)

A hybrid cost-sensitive ensemble for imbalanced breast thermogram classification. - Bartosz Krawczyk; Gerald Schaefer; Michal Wozniak 001 (Artif. Intell. Medicine, 2015)

Multidimensional data classification with chordal distance based kernel and Support Vector Machines. - Boguslaw Cyganek; Bartosz Krawczyk; Michal Wozniak 001 (Eng. Appl. Artif. Intell., 2015)

One-class classifier ensemble pruning and weighting with firefly algorithm. - Bartosz Krawczyk (Neurocomputing, 2015)

Data stream classification and big data analytics. - Bartosz Krawczyk; Jerzy Stefanowski; Michal Wozniak 001 (Neurocomputing, 2015)

Incremental weighted one-class classifier for mining stationary data streams. - Bartosz Krawczyk; Michal Wozniak 001 (J. Comput. Sci., 2015)

Forming Ensembles of Soft One-Class Classifiers with Weighted Bagging. - Bartosz Krawczyk (New Gener. Comput., 2015)

Hybrid Ensemble Machine Learning for Complex and Dynamic Data. - Bartosz Krawczyk; Bogdan Trawinski (New Gener. Comput., 2015)

On the usefulness of one-class classifier ensembles for decomposition of multi-class problems. - Bartosz Krawczyk; Michal Wozniak 001; Francisco Herrera (Pattern Recognit., 2015)

One-class classifiers with incremental learning and forgetting for data streams with concept drift. - Bartosz Krawczyk; Michal Wozniak 001 (Soft Comput., 2015)

Hybrid One-Class Ensemble for High-Dimensional Data Classification. - Bartosz Krawczyk (ACIIDS (2), 2016)

Ensemble of One-Dimensional Classifiers for Hyperspectral Image Analysis. - Pawel Ksieniewicz; Bartosz Krawczyk; Michal Wozniak 001 (DMBD, 2016)

Forming Classifier Ensembles with Deterministic Feature Subspaces. - Michal Koziarski; Bartosz Krawczyk; Michal Wozniak 001 (FedCSIS, 2016)

Tackling label noise with multi-class decomposition using fuzzy one-class support vector machines. - Bartosz Krawczyk; José A. Sáez; Michal Wozniak 001 (FUZZ-IEEE, 2016)

GPU-Accelerated Extreme Learning Machines for Imbalanced Data Streams with Concept Drift. - Bartosz Krawczyk (ICCS, 2016)

Workshop on Nonstationary Models of Pattern Recognition and Classifier Combinations. - Michal Wozniak 001; Bartosz Krawczyk (ICCS, 2016)

Cost-sensitive one-vs-one ensemble for multi-class imbalanced data. - Bartosz Krawczyk (IJCNN, 2016)

A Survey of Big Data Issues in Electronic Health Record Analysis. - Boguslaw Cyganek; Manuel Graña; Bartosz Krawczyk; Andrzej Kasprzak; Piotr Porwik; Krzysztof Walkowiak; Michal Wozniak 001 (Appl. Artif. Intell., 2016)

On the Influence of Class Noise in Medical Data Classification: Treatment Using Noise Filtering Methods. - José A. Sáez; Bartosz Krawczyk; Michal Wozniak 001 (Appl. Artif. Intell., 2016)

Evolutionary undersampling boosting for imbalanced classification of breast cancer malignancy. - Bartosz Krawczyk; Mikel Galar; Lukasz Jelen; Francisco Herrera (Appl. Soft Comput., 2016)

Untrained weighted classifier combination with embedded ensemble pruning. - Bartosz Krawczyk; Michal Wozniak 001 (Neurocomputing, 2016)

Dynamic classifier selection for one-class classification. - Bartosz Krawczyk; Michal Wozniak 001 (Knowl. Based Syst., 2016)

Empowering one-vs-one decomposition with ensemble learning for multi-class imbalanced data. - Zhongliang Zhang 001; Bartosz Krawczyk; Salvador García 001; Alejandro Rosales-Pérez; Francisco Herrera (Knowl. Based Syst., 2016)

Learning from imbalanced data: open challenges and future directions. - Bartosz Krawczyk (Prog. Artif. Intell., 2016)

Analyzing the oversampling of different classes and types of examples in multi-class imbalanced datasets. - José A. Sáez; Bartosz Krawczyk; Michal Wozniak 001 (Pattern Recognit., 2016)

Combining Active Learning and Self-Labeling for Data Stream Mining. - Lukasz Korycki; Bartosz Krawczyk (CORES, 2017)

Radial-Based Approach to Imbalanced Data Oversampling. - Michal Koziarski; Bartosz Krawczyk; Michal Wozniak 001 (HAIS, 2017)

Sentiment Classification from Multi-class Imbalanced Twitter Data Using Binarization. - Bartosz Krawczyk; Bridget T. McInnes; Alberto Cano 001 (HAIS, 2017)

Immersive browsing in an image sphere. - Gerald Schaefer; Mateusz Budnik; Bartosz Krawczyk (IMCOM, 2017)

Online query by committee for active learning from drifting data streams. - Bartosz Krawczyk; Michal Wozniak 001 (IJCNN, 2017)

Cost-Sensitive Perceptron Decision Trees for Imbalanced Drifting Data Streams. - Bartosz Krawczyk; Przemyslaw Skryjomski (ECML/PKDD (2), 2017)

Influence of minority class instance types on SMOTE imbalanced data oversampling. - Przemyslaw Skryjomski; Bartosz Krawczyk (LIDTA@PKDD/ECML, 2017)

Learning with Imbalanced Domains: Preface. - Luís Torgo; Bartosz Krawczyk; Paula Branco; Nuno Moniz (LIDTA@PKDD/ECML, 2017)

Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble. - Jerzy Kowalski; Bartosz Krawczyk; Michal Wozniak 001 (Eng. Appl. Artif. Intell., 2017)

A survey on data preprocessing for data stream mining: Current status and future directions. - Sergio Ramírez-Gallego; Bartosz Krawczyk; Salvador García 001; Michal Wozniak 001; Francisco Herrera (Neurocomputing, 2017)

Ensemble learning for data stream analysis: A survey. - Bartosz Krawczyk; Leandro L. Minku; João Gama 001; Jerzy Stefanowski; Michal Wozniak 001 (Inf. Fusion, 2017)

Active and adaptive ensemble learning for online activity recognition from data streams. - Bartosz Krawczyk (Knowl. Based Syst., 2017)

The deterministic subspace method for constructing classifier ensembles. - Michal Koziarski; Bartosz Krawczyk; Michal Wozniak 001 (Pattern Anal. Appl., 2017)

Selecting locally specialised classifiers for one-class classification ensembles. - Bartosz Krawczyk; Boguslaw Cyganek (Pattern Anal. Appl., 2017)

Nearest Neighbor Classification for High-Speed Big Data Streams Using Spark. - Sergio Ramírez-Gallego; Bartosz Krawczyk; Salvador García 001; Michal Wozniak 001; José Manuel Benítez 001; Francisco Herrera (IEEE Trans. Syst. Man Cybern. Syst., 2017)

Learning from Imbalanced Data Sets - Alberto Fernández 001; Salvador García 001; Mikel Galar; Ronaldo C. Prati; Bartosz Krawczyk; Francisco Herrera (Springer, 2018)

Clustering-Driven and Dynamically Diversified Ensemble for Drifting Data Streams. - Lukasz Korycki; Bartosz Krawczyk (IEEE BigData, 2018)

Combining active learning with concept drift detection for data stream mining. - Bartosz Krawczyk; Bernhard Pfahringer; Michal Wozniak 001 (IEEE BigData, 2018)

Learning Classification Rules with Differential Evolution for High-Speed Data Stream Mining on GPU s. - Alberto Cano 001; Bartosz Krawczyk (CEC, 2018)

An Empirical Insight Into Concept Drift Detectors Ensemble Strategies. - Andrzej Lapinski; Bartosz Krawczyk; Pawel Ksieniewicz; Michal Wozniak 001 (CEC, 2018)

Addressing Local Class Imbalance in Balanced Datasets with Dynamic Impurity Decision Trees. - Andriy Mulyar; Bartosz Krawczyk (DS, 2018)

Multi-class Imbalanced Data Oversampling for Vertebral Column Pathologies Classification. - José A. Sáez; Héctor Quintián; Bartosz Krawczyk; Michal Wozniak 001; Emilio Corchado (HAIS, 2018)

Synthetic Oversampling with the Majority Class: A New Perspective on Handling Extreme Imbalance. - Shiven Sharma; Colin Bellinger; Bartosz Krawczyk; Osmar R. Zaïane; Nathalie Japkowicz (ICDM, 2018)

Selecting local ensembles for multi-class imbalanced data classification. - Bartosz Krawczyk; Alberto Cano 001; Michal Wozniak 001 (IJCNN, 2018)

2nd Workshop on Learning with Imbalanced Domains: Preface. - Luís Torgo; Stan Matwin; Nathalie Japkowicz; Bartosz Krawczyk; Nuno Moniz; Paula Branco (LIDTA@ECML/PKDD, 2018)

Leveraging Ensemble Pruning for Imbalanced Data Classification. - Bartosz Krawczyk; Michal Wozniak 001 (SMC, 2018)

Online ensemble learning with abstaining classifiers for drifting and noisy data streams. - Bartosz Krawczyk; Alberto Cano 001 (Appl. Soft Comput., 2018)

Ensemble of Extreme Learning Machines with trained classifier combination and statistical features for hyperspectral data. - Pawel Ksieniewicz; Bartosz Krawczyk; Michal Wozniak 001 (Neurocomputing, 2018)

Dynamic ensemble selection for multi-class classification with one-class classifiers. - Bartosz Krawczyk; Mikel Galar; Michal Wozniak 001; Humberto Bustince; Francisco Herrera (Pattern Recognit., 2018)

Local ensemble learning from imbalanced and noisy data for word sense disambiguation. - Bartosz Krawczyk; Bridget T. McInnes (Pattern Recognit., 2018)

Active Learning with Abstaining Classifiers for Imbalanced Drifting Data Streams. - Lukasz Korycki; Alberto Cano 001; Bartosz Krawczyk (IEEE BigData, 2019)

Bagging Using Instance-Level Difficulty for Multi-Class Imbalanced Big Data Classification on Spark. - William C. Sleeman IV; Bartosz Krawczyk (IEEE BigData, 2019)

Unsupervised Drift Detector Ensembles for Data Stream Mining. - Lukasz Korycki; Bartosz Krawczyk (DSAA, 2019)

On the Role of Cost-Sensitive Learning in Imbalanced Data Oversampling. - Bartosz Krawczyk; Michal Wozniak 001 (ICCS (3), 2019)

Adaptive Ensemble Active Learning for Drifting Data Stream Mining. - Bartosz Krawczyk; Alberto Cano 001 (IJCAI, 2019)

Addressing the Overlapping Data Problem in Classification Using the One-vs-One Decomposition Strategy. - José A. Sáez; Mikel Galar; Bartosz Krawczyk (IEEE Access, 2019)

Uniqueness of Medical Data Mining: How the new technologies and data they generate are transforming medicine. - Krzysztof J. Cios; Bartosz Krawczyk; Jacquelyne Cios; Kevin J. Staley (CoRR, 2019)

Towards highly accurate coral texture images classification using deep convolutional neural networks and data augmentation. - Anabel Gómez-Ríos; Siham Tabik; Julián Luengo; A. S. M. Shihavuddin; Bartosz Krawczyk; Francisco Herrera (Expert Syst. Appl., 2019)

Monotonic classification: An overview on algorithms, performance measures and data sets. - José Ramón Cano; Pedro Antonio Gutiérrez; Bartosz Krawczyk; Michal Wozniak 001; Salvador García 001 (Neurocomputing, 2019)

Radial-Based oversampling for noisy imbalanced data classification. - Michal Koziarski; Bartosz Krawczyk; Michal Wozniak 001 (Neurocomputing, 2019)

Speeding up k-Nearest Neighbors classifier for large-scale multi-label learning on GPUs. - Przemyslaw Skryjomski; Bartosz Krawczyk; Alberto Cano 001 (Neurocomputing, 2019)

Instance reduction for one-class classification. - Bartosz Krawczyk; Isaac Triguero; Salvador García 001; Michal Wozniak 001; Francisco Herrera (Knowl. Inf. Syst., 2019)

Evolving rule-based classifiers with genetic programming on GPUs for drifting data streams. - Alberto Cano 001; Bartosz Krawczyk (Pattern Recognit., 2019)

Multi-Label Punitive kNN with Self-Adjusting Memory for Drifting Data Streams. - Martha I. Roseberry; Bartosz Krawczyk; Alberto Cano 001 (ACM Trans. Knowl. Discov. Data, 2019)

Online Oversampling for Sparsely Labeled Imbalanced and Non-Stationary Data Streams. - Lukasz Korycki; Bartosz Krawczyk (IJCNN, 2020)

Adaptive Deep Forest for Online Learning from Drifting Data Streams. - Lukasz Korycki; Bartosz Krawczyk (CoRR, 2020)

A Machine Learning method for relabeling arbitrary DICOM structure sets to TG-263 defined labels. - William C. Sleeman IV; Joseph Nalluri; Khajamoinuddin Syed; Preetam Ghosh; Bartosz Krawczyk; Michael Hagan; Jatinder Palta; Rishabh Kapoor (J. Biomed. Informatics, 2020)

Combined Cleaning and Resampling algorithm for multi-class imbalanced data with label noise. - Michal Koziarski; Michal Wozniak 001; Bartosz Krawczyk (Knowl. Based Syst., 2020)

Kappa Updated Ensemble for drifting data stream mining. - Alberto Cano 001; Bartosz Krawczyk (Mach. Learn., 2020)

Radial-Based Oversampling for Multiclass Imbalanced Data Classification. - Bartosz Krawczyk; Michal Koziarski; Michal Wozniak 001 (IEEE Trans. Neural Networks Learn. Syst., 2020)

On the combined effect of class imbalance and concept complexity in deep learning. - Kushankur Ghosh; Colin Bellinger; Roberto Corizzo; Bartosz Krawczyk; Nathalie Japkowicz (IEEE BigData, 2021)

Class-Incremental Experience Replay for Continual Learning Under Concept Drift. - Lukasz Korycki; Bartosz Krawczyk (CVPR Workshops, 2021)

Concept Drift Detection from Multi-Class Imbalanced Data Streams. - Lukasz Korycki; Bartosz Krawczyk (ICDE, 2021)

Undersampling with Support Vectors for Multi-Class Imbalanced Data Classification. - Bartosz Krawczyk; Colin Bellinger; Roberto Corizzo; Nathalie Japkowicz (IJCNN, 2021)

Evaluating and Explaining Generative Adversarial Networks for Continual Learning under Concept Drift. - Filip Guzy; Michal Wozniak 001; Bartosz Krawczyk (ICDM (Workshops), 2021)

Low-Dimensional Representation Learning from Imbalanced Data Streams. - Lukasz Korycki; Bartosz Krawczyk (PAKDD (1), 2021)

Locally Linear Support Vector Machines for Imbalanced Data Classification. - Bartosz Krawczyk; Alberto Cano 001 (PAKDD (1), 2021)

Streaming Decision Trees for Lifelong Learning. - Lukasz Korycki; Bartosz Krawczyk (ECML/PKDD (1), 2021)

XRRpred: accurate predictor of crystal structure quality from protein sequence. - Sina Ghadermarzi; Bartosz Krawczyk; Jiangning Song; Lukasz A. Kurgan (Bioinform., 2021)

Imbalanced Big Data Oversampling: Taxonomy, Algorithms, Software, Guidelines and Future Directions. - William C. Sleeman IV; Bartosz Krawczyk (CoRR, 2021)

Mining Drifting Data Streams on a Budget: Combining Active Learning with Self-Labeling. - Lukasz Korycki; Bartosz Krawczyk (CoRR, 2021)

Self-adjusting k nearest neighbors for continual learning from multi-label drifting data streams. - Martha I. Roseberry; Bartosz Krawczyk; Youcef Djenouri; Alberto Cano 001 (Neurocomputing, 2021)

Multi-class imbalanced big data classification on Spark. - William C. Sleeman IV; Bartosz Krawczyk (Knowl. Based Syst., 2021)

Tensor decision trees for continual learning from drifting data streams. - Bartosz Krawczyk (Mach. Learn., 2021)

Towards A Holistic View of Bias in Machine Learning: Bridging Algorithmic Fairness and Imbalanced Learning. - Damien Dablain; Bartosz Krawczyk; Nitesh V. Chawla (CoRR, 2022)

Interpretable ML for Imbalanced Data. - Damien A. Dablain; Colin Bellinger; Bartosz Krawczyk; David W. Aha; Nitesh V. Chawla (CoRR, 2022)

ROSE: robust online self-adjusting ensemble for continual learning on imbalanced drifting data streams. - Alberto Cano 001; Bartosz Krawczyk (Mach. Learn., 2022)

Instance exploitation for learning temporary concepts from sparsely labeled drifting data streams. - Lukasz Korycki; Bartosz Krawczyk (Pattern Recognit., 2022)

Efficient Augmentation for Imbalanced Deep Learning. - Damien A. Dablain; Colin Bellinger; Bartosz Krawczyk; Nitesh V. Chawla (ICDE, 2023)

Class-Aware Neural Networks for Efficient Intrusion Detection on Edge Devices. - Mohammed Ayyat; Tamer Nadeem; Bartosz Krawczyk (SECON, 2023)

DeepSMOTE: Fusing Deep Learning and SMOTE for Imbalanced Data. - Damien Dablain; Bartosz Krawczyk; Nitesh V. Chawla (IEEE Trans. Neural Networks Learn. Syst., 2023)

Adversarial concept drift detection under poisoning attacks for robust data stream mining. - Lukasz Korycki; Bartosz Krawczyk (Mach. Learn., 2023)

Class-Incremental Mixture of Gaussians for Deep Continual Learning. - Lukasz Korycki; Bartosz Krawczyk (CVPR Workshops, 2024)

Continual Learning with Weight Interpolation. - Jedrzej Kozal; Jan Wasilewski; Bartosz Krawczyk; Michal Wozniak 001 (CVPR Workshops, 2024)

Combining Active Learning and Self-Labeling for Deep Learning from Data Streams. - Jan Wasilewski; Michal Wozniak 001; Bartosz Krawczyk (ICDM (Workshops), 2024)

Balanced Gradient Sample Retrieval for Enhanced Knowledge Retention in Proxy-based Continual Learning. - Hongye Xu; Jan Wasilewski; Bartosz Krawczyk (CoRR, 2024)

ClassyNet: Class-Aware Early-Exit Neural Networks for Edge Devices. - Mohammed Ayyat; Tamer Nadeem; Bartosz Krawczyk (IEEE Internet Things J., 2024)

Correction: Adversarial concept drift detection under poisoning attacks for robust data stream mining. - Lukasz Korycki; Bartosz Krawczyk (Mach. Learn., 2024)

Understanding imbalanced data: XAI & interpretable ML framework. - Damien Dablain; Colin Bellinger; Bartosz Krawczyk; David W. Aha; Nitesh V. Chawla (Mach. Learn., 2024)

A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework. - Gabriel Aguiar; Bartosz Krawczyk; Alberto Cano 001 (Mach. Learn., 2024)

The class imbalance problem in deep learning. - Kushankur Ghosh; Colin Bellinger; Roberto Corizzo; Paula Branco; Bartosz Krawczyk; Nathalie Japkowicz (Mach. Learn., 2024)

Improved KD-tree based imbalanced big data classification and oversampling for MapReduce platforms. - William C. Sleeman; Martha I. Roseberry; Preetam Ghosh; Alberto Cano 001; Bartosz Krawczyk (Appl. Intell., 2024)

What is the role of memorization in Continual Learning? - Jedrzej Kozal; Jan Wasilewski; Alif Ashrafee; Bartosz Krawczyk; Michal Wozniak 001 (CoRR, 2025)

Holistic Continual Learning under Concept Drift with Adaptive Memory Realignment. - Alif Ashrafee; Jedrzej Kozal; Michal Wozniak 001; Bartosz Krawczyk (CoRR, 2025)

OpenScout v1.1 mobile robot: a case study on open hardware continuation. - Bartosz Krawczyk; Ahmed Elbary; Robbie Cato; Jagdish Patil; Kaung Myat; Anyeh Ndi-Tah; Nivetha Sakthivel; Mark Crampton; Gautham Das; Charles Fox (CoRR, 2025)