Bartosz Krawczyk

ORCID

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 105

Top Venues

Publications

Damien Dablain, Colin Bellinger, Bartosz Krawczyk, David W. Aha, Nitesh V. Chawla
Understanding imbalanced data: XAI & interpretable ML framework. Mach. Learn. 113 (6) (2024)
Gabriel Aguiar, Bartosz Krawczyk, Alberto Cano
A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework. Mach. Learn. 113 (7) (2024)
Jedrzej Kozal, Jan Wasilewski, Bartosz Krawczyk, Michal Wozniak
Continual Learning with Weight Interpolation. CoRR (2024)
Kushankur Ghosh, Colin Bellinger, Roberto Corizzo, Paula Branco, Bartosz Krawczyk, Nathalie Japkowicz
The class imbalance problem in deep learning. Mach. Learn. 113 (7) (2024)
Lukasz Korycki, Bartosz Krawczyk
Correction: Adversarial concept drift detection under poisoning attacks for robust data stream mining. Mach. Learn. 113 (5) (2024)
Mohammed Ayyat, Tamer Nadeem, Bartosz Krawczyk
ClassyNet: Class-Aware Early-Exit Neural Networks for Edge Devices. IEEE Internet Things J. 11 (9) (2024)
Lukasz Korycki, Bartosz Krawczyk
Adversarial concept drift detection under poisoning attacks for robust data stream mining. Mach. Learn. 112 (10) (2023)
Damien Dablain, Bartosz Krawczyk, Nitesh V. Chawla
DeepSMOTE: Fusing Deep Learning and SMOTE for Imbalanced Data. IEEE Trans. Neural Networks Learn. Syst. 34 (9) (2023)
Damien A. Dablain, Colin Bellinger, Bartosz Krawczyk, Nitesh V. Chawla
Efficient Augmentation for Imbalanced Deep Learning. ICDE (2023)
Lukasz Korycki, Bartosz Krawczyk
Class-Incremental Mixture of Gaussians for Deep Continual Learning. CoRR (2023)
Mohammed Ayyat, Tamer Nadeem, Bartosz Krawczyk
Class-Aware Neural Networks for Efficient Intrusion Detection on Edge Devices. SECON (2023)
Alberto Cano, Bartosz Krawczyk
ROSE: robust online self-adjusting ensemble for continual learning on imbalanced drifting data streams. Mach. Learn. 111 (7) (2022)
Damien Dablain, Colin Bellinger, Bartosz Krawczyk, Nitesh V. Chawla
Efficient Augmentation for Imbalanced Deep Learning. CoRR (2022)
Damien Dablain, Bartosz Krawczyk, Nitesh V. Chawla
Towards A Holistic View of Bias in Machine Learning: Bridging Algorithmic Fairness and Imbalanced Learning. CoRR (2022)
Gabriel Aguiar, Bartosz Krawczyk, Alberto Cano
A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework. CoRR (2022)
Lukasz Korycki, Bartosz Krawczyk
Instance exploitation for learning temporary concepts from sparsely labeled drifting data streams. Pattern Recognit. 129 (2022)
Damien A. Dablain, Colin Bellinger, Bartosz Krawczyk, David W. Aha, Nitesh V. Chawla
Interpretable ML for Imbalanced Data. CoRR (2022)
Martha Roseberry, Bartosz Krawczyk, Youcef Djenouri, Alberto Cano
Self-adjusting k nearest neighbors for continual learning from multi-label drifting data streams. Neurocomputing 442 (2021)
Lukasz Korycki, Bartosz Krawczyk
Class-Incremental Experience Replay for Continual Learning under Concept Drift. CoRR (2021)
William C. Sleeman IV, Bartosz Krawczyk
Multi-class imbalanced big data classification on Spark. Knowl. Based Syst. 212 (2021)
Bartosz Krawczyk
Tensor decision trees for continual learning from drifting data streams. Mach. Learn. 110 (11) (2021)
Bartosz Krawczyk, Colin Bellinger, Roberto Corizzo, Nathalie Japkowicz
Undersampling with Support Vectors for Multi-Class Imbalanced Data Classification. IJCNN (2021)
Lukasz Korycki, Bartosz Krawczyk
Concept Drift Detection from Multi-Class Imbalanced Data Streams. ICDE (2021)
Lukasz Korycki, Bartosz Krawczyk
Low-Dimensional Representation Learning from Imbalanced Data Streams. PAKDD (1) (2021)
Lukasz Korycki, Bartosz Krawczyk
Mining Drifting Data Streams on a Budget: Combining Active Learning with Self-Labeling. CoRR (2021)
Kushankur Ghosh, Colin Bellinger, Roberto Corizzo, Bartosz Krawczyk, Nathalie Japkowicz
On the combined effect of class imbalance and concept complexity in deep learning. IEEE BigData (2021)
Lukasz Korycki, Bartosz Krawczyk
Class-Incremental Experience Replay for Continual Learning Under Concept Drift. CVPR Workshops (2021)
William C. Sleeman IV, Bartosz Krawczyk
Imbalanced Big Data Oversampling: Taxonomy, Algorithms, Software, Guidelines and Future Directions. CoRR (2021)
Damien Dablain, Bartosz Krawczyk, Nitesh V. Chawla
DeepSMOTE: Fusing Deep Learning and SMOTE for Imbalanced Data. CoRR (2021)
Sina Ghadermarzi, Bartosz Krawczyk, Jiangning Song, Lukasz A. Kurgan
XRRpred: accurate predictor of crystal structure quality from protein sequence. Bioinform. 37 (23) (2021)
Lukasz Korycki, Bartosz Krawczyk
Concept Drift Detection from Multi-Class Imbalanced Data Streams. CoRR (2021)
Lukasz Korycki, Bartosz Krawczyk
Streaming Decision Trees for Lifelong Learning. ECML/PKDD (1) (2021)
Bartosz Krawczyk, Alberto Cano
Locally Linear Support Vector Machines for Imbalanced Data Classification. PAKDD (1) (2021)
Filip Guzy, Michal Wozniak, Bartosz Krawczyk
Evaluating and Explaining Generative Adversarial Networks for Continual Learning under Concept Drift. ICDM (Workshops) (2021)
Bartosz Krawczyk
Tensor Decision Trees for Continual Learning from Drifting Data Streams. DSAA (2021)
Kushankur Ghosh, Colin Bellinger, Roberto Corizzo, Bartosz Krawczyk, Nathalie Japkowicz
On the combined effect of class imbalance and concept complexity in deep learning. CoRR (2021)
Lukasz Korycki, Bartosz Krawczyk
Adaptive Deep Forest for Online Learning from Drifting Data Streams. CoRR (2020)
Michal Koziarski, Michal Wozniak, Bartosz Krawczyk
Combined Cleaning and Resampling Algorithm for Multi-Class Imbalanced Data with Label Noise. CoRR (2020)
Alberto Cano, Bartosz Krawczyk
Kappa Updated Ensemble for drifting data stream mining. Mach. Learn. 109 (1) (2020)
Lukasz Korycki, Bartosz Krawczyk
Adversarial Concept Drift Detection under Poisoning Attacks for Robust Data Stream Mining. CoRR (2020)
William C. Sleeman IV, Joseph Nalluri, Khajamoinuddin Syed, Preetam Ghosh, Bartosz Krawczyk, Michael Hagan, Jatinder Palta, Rishabh Kapoor
A Machine Learning method for relabeling arbitrary DICOM structure sets to TG-263 defined labels. J. Biomed. Informatics 109 (2020)
Bartosz Krawczyk, Michal Koziarski, Michal Wozniak
Radial-Based Oversampling for Multiclass Imbalanced Data Classification. IEEE Trans. Neural Networks Learn. Syst. 31 (8) (2020)
Lukasz Korycki, Bartosz Krawczyk
Online Oversampling for Sparsely Labeled Imbalanced and Non-Stationary Data Streams. IJCNN (2020)
Lukasz Korycki, Bartosz Krawczyk
Instance exploitation for learning temporary concepts from sparsely labeled drifting data streams. CoRR (2020)
Michal Koziarski, Michal Wozniak, Bartosz Krawczyk
Combined Cleaning and Resampling algorithm for multi-class imbalanced data with label noise. Knowl. Based Syst. 204 (2020)
Martha Roseberry, Bartosz Krawczyk, Alberto Cano
Multi-Label Punitive kNN with Self-Adjusting Memory for Drifting Data Streams. ACM Trans. Knowl. Discov. Data 13 (6) (2019)
William C. Sleeman IV, Bartosz Krawczyk
Bagging Using Instance-Level Difficulty for Multi-Class Imbalanced Big Data Classification on Spark. IEEE BigData (2019)
José Ramón Cano, Pedro Antonio Gutiérrez, Bartosz Krawczyk, Michal Wozniak, Salvador García
Monotonic classification: An overview on algorithms, performance measures and data sets. Neurocomputing 341 (2019)
Przemyslaw Skryjomski, Bartosz Krawczyk, Alberto Cano
-Nearest Neighbors classifier for large-scale multi-label learning on GPUs. Neurocomputing 354 (2019)
Michal Koziarski, Bartosz Krawczyk, Michal Wozniak
Radial-Based oversampling for noisy imbalanced data classification. Neurocomputing 343 (2019)
Bartosz Krawczyk, Isaac Triguero, Salvador García, Michal Wozniak, Francisco Herrera
Instance reduction for one-class classification. Knowl. Inf. Syst. 59 (3) (2019)
Anabel Gómez-Ríos, Siham Tabik, Julián Luengo, A. S. M. Shihavuddin, Bartosz Krawczyk, Francisco Herrera
Towards highly accurate coral texture images classification using deep convolutional neural networks and data augmentation. Expert Syst. Appl. 118 (2019)
Alberto Cano, Bartosz Krawczyk
Evolving rule-based classifiers with genetic programming on GPUs for drifting data streams. Pattern Recognit. 87 (2019)
Bartosz Krawczyk, Michal Wozniak
On the Role of Cost-Sensitive Learning in Imbalanced Data Oversampling. ICCS (3) (2019)
Lukasz Korycki, Bartosz Krawczyk
Unsupervised Drift Detector Ensembles for Data Stream Mining. DSAA (2019)
José A. Sáez, Mikel Galar, Bartosz Krawczyk
Addressing the Overlapping Data Problem in Classification Using the One-vs-One Decomposition Strategy. IEEE Access 7 (2019)
Lukasz Korycki, Alberto Cano, Bartosz Krawczyk
Active Learning with Abstaining Classifiers for Imbalanced Drifting Data Streams. IEEE BigData (2019)
Bartosz Krawczyk, Alberto Cano
Adaptive Ensemble Active Learning for Drifting Data Stream Mining. IJCAI (2019)
Krzysztof J. Cios, Bartosz Krawczyk, Jacquelyne Cios, Kevin J. Staley
Uniqueness of Medical Data Mining: How the new technologies and data they generate are transforming medicine. CoRR (2019)
Anabel Gómez-Ríos, Siham Tabik, Julián Luengo, A. S. M. Shihavuddin, Bartosz Krawczyk, Francisco Herrera
Towards Highly Accurate Coral Texture Images Classification Using Deep Convolutional Neural Networks and Data Augmentation. CoRR (2018)
Andriy Mulyar, Bartosz Krawczyk
Addressing Local Class Imbalance in Balanced Datasets with Dynamic Impurity Decision Trees. DS (2018)
Bartosz Krawczyk, Bridget T. McInnes
Local ensemble learning from imbalanced and noisy data for word sense disambiguation. Pattern Recognit. 78 (2018)
José Ramón Cano, Pedro Antonio Gutiérrez, Bartosz Krawczyk, Michal Wozniak, Salvador García
Monotonic classification: an overview on algorithms, performance measures and data sets. CoRR (2018)
Shiven Sharma, Colin Bellinger, Bartosz Krawczyk, Osmar R. Zaïane, Nathalie Japkowicz
Synthetic Oversampling with the Majority Class: A New Perspective on Handling Extreme Imbalance. ICDM (2018)
Lukasz Korycki, Bartosz Krawczyk
Clustering-Driven and Dynamically Diversified Ensemble for Drifting Data Streams. IEEE BigData (2018)
Andrzej Lapinski, Bartosz Krawczyk, Pawel Ksieniewicz, Michal Wozniak
An Empirical Insight Into Concept Drift Detectors Ensemble Strategies. CEC (2018)
Alberto Cano, Bartosz Krawczyk
Learning Classification Rules with Differential Evolution for High-Speed Data Stream Mining on GPU s. CEC (2018)
Luís Torgo, Stan Matwin, Nathalie Japkowicz, Bartosz Krawczyk, Nuno Moniz, Paula Branco
2nd Workshop on Learning with Imbalanced Domains: Preface. LIDTA@ECML/PKDD (2018)
Bartosz Krawczyk, Michal Wozniak
Leveraging Ensemble Pruning for Imbalanced Data Classification. SMC (2018)
Bartosz Krawczyk, Alberto Cano, Michal Wozniak
Selecting local ensembles for multi-class imbalanced data classification. IJCNN (2018)
Pawel Ksieniewicz, Bartosz Krawczyk, Michal Wozniak
Ensemble of Extreme Learning Machines with trained classifier combination and statistical features for hyperspectral data. Neurocomputing 271 (2018)
Bartosz Krawczyk, Bernhard Pfahringer, Michal Wozniak
Combining active learning with concept drift detection for data stream mining. IEEE BigData (2018)
Bartosz Krawczyk, Mikel Galar, Michal Wozniak, Humberto Bustince, Francisco Herrera
Dynamic ensemble selection for multi-class classification with one-class classifiers. Pattern Recognit. 83 (2018)
José A. Sáez, Héctor Quintián, Bartosz Krawczyk, Michal Wozniak, Emilio Corchado
Multi-class Imbalanced Data Oversampling for Vertebral Column Pathologies Classification. HAIS (2018)
Bartosz Krawczyk, Alberto Cano
Online ensemble learning with abstaining classifiers for drifting and noisy data streams. Appl. Soft Comput. 68 (2018)
Jerzy Kowalski, Bartosz Krawczyk, Michal Wozniak
Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble. Eng. Appl. Artif. Intell. 57 (2017)
Sergio Ramírez-Gallego, Bartosz Krawczyk, Salvador García, Michal Wozniak, Francisco Herrera
A survey on data preprocessing for data stream mining: Current status and future directions. Neurocomputing 239 (2017)
Bartosz Krawczyk, Boguslaw Cyganek
Selecting locally specialised classifiers for one-class classification ensembles. Pattern Anal. Appl. 20 (2) (2017)
Sergio Ramírez-Gallego, Bartosz Krawczyk, Salvador García, Michal Wozniak, José Manuel Benítez, Francisco Herrera
Nearest Neighbor Classification for High-Speed Big Data Streams Using Spark. IEEE Trans. Syst. Man Cybern. Syst. 47 (10) (2017)
Bartosz Krawczyk, Przemyslaw Skryjomski
Cost-Sensitive Perceptron Decision Trees for Imbalanced Drifting Data Streams. ECML/PKDD (2) (2017)
Gerald Schaefer, Mateusz Budnik, Bartosz Krawczyk
Immersive browsing in an image sphere. IMCOM (2017)
Bartosz Krawczyk, Leandro L. Minku, João Gama, Jerzy Stefanowski, Michal Wozniak
Ensemble learning for data stream analysis: A survey. Inf. Fusion 37 (2017)
Bartosz Krawczyk, Bridget T. McInnes, Alberto Cano
Sentiment Classification from Multi-class Imbalanced Twitter Data Using Binarization. HAIS (2017)
Michal Koziarski, Bartosz Krawczyk, Michal Wozniak
Radial-Based Approach to Imbalanced Data Oversampling. HAIS (2017)
Michal Koziarski, Bartosz Krawczyk, Michal Wozniak
The deterministic subspace method for constructing classifier ensembles. Pattern Anal. Appl. 20 (4) (2017)
Bartosz Krawczyk, Michal Wozniak
Online query by committee for active learning from drifting data streams. IJCNN (2017)
Luís Torgo, Bartosz Krawczyk, Paula Branco, Nuno Moniz
Learning with Imbalanced Domains: Preface. LIDTA@PKDD/ECML (2017)
Lukasz Korycki, Bartosz Krawczyk
Combining Active Learning and Self-Labeling for Data Stream Mining. CORES (2017)
Bartosz Krawczyk
Active and adaptive ensemble learning for online activity recognition from data streams. Knowl. Based Syst. 138 (2017)
Przemyslaw Skryjomski, Bartosz Krawczyk
Influence of minority class instance types on SMOTE imbalanced data oversampling. LIDTA@PKDD/ECML (2017)
Bartosz Krawczyk
Learning from imbalanced data: open challenges and future directions. Prog. Artif. Intell. 5 (4) (2016)
Pawel Ksieniewicz, Bartosz Krawczyk, Michal Wozniak
Ensemble of One-Dimensional Classifiers for Hyperspectral Image Analysis. DMBD (2016)
Zhongliang Zhang, Bartosz Krawczyk, Salvador García, Alejandro Rosales-Pérez, Francisco Herrera
Empowering one-vs-one decomposition with ensemble learning for multi-class imbalanced data. Knowl. Based Syst. 106 (2016)
Bartosz Krawczyk
Cost-sensitive one-vs-one ensemble for multi-class imbalanced data. IJCNN (2016)
Bartosz Krawczyk, Michal Wozniak
Untrained weighted classifier combination with embedded ensemble pruning. Neurocomputing 196 (2016)
José A. Sáez, Bartosz Krawczyk, Michal Wozniak
Analyzing the oversampling of different classes and types of examples in multi-class imbalanced datasets. Pattern Recognit. 57 (2016)
Bartosz Krawczyk, José A. Sáez, Michal Wozniak
Tackling label noise with multi-class decomposition using fuzzy one-class support vector machines. FUZZ-IEEE (2016)
Boguslaw Cyganek, Manuel Graña, Bartosz Krawczyk, Andrzej Kasprzak, Piotr Porwik, Krzysztof Walkowiak, Michal Wozniak
A Survey of Big Data Issues in Electronic Health Record Analysis. Appl. Artif. Intell. 30 (6) (2016)
Bartosz Krawczyk
Hybrid One-Class Ensemble for High-Dimensional Data Classification. ACIIDS (2) (2016)
Michal Koziarski, Bartosz Krawczyk, Michal Wozniak
Forming Classifier Ensembles with Deterministic Feature Subspaces. FedCSIS (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Bartosz Krawczyk