publications

2022

  1. DeepSMOTE: Fusing Deep Learning and SMOTE for Imbalanced Data
    Damien Dablain, Bartosz Krawczyk, and Nitesh V. Chawla
    IEEE Transactions on Neural Networks and Learning Systems, 2022
    HTML
  2. The class imbalance problem in deep learning
    Kushankur Ghosh, Colin Bellinger, Roberto Corizzo, and 3 more authors
    Machine Learning, 2022
    HTML
  3. Adversarial concept drift detection under poisoning attacks for robust data stream mining
    Lukasz Korycki, and Bartosz Krawczyk
    Machine Learning, 2022
    HTML
  4. ROSE: robust online self-adjusting ensemble for continual learning on imbalanced drifting data streams
    Alberto Cano, and Bartosz Krawczyk
    Machine Learning, 2022
    HTML
  5. Instance exploitation for learning temporary concepts from sparsely labeled drifting data streams
    Lukasz Korycki, and Bartosz Krawczyk
    Pattern Recognition, 2022
    HTML

2021

  1. XRRpred: accurate predictor of crystal structure quality from protein sequence
    Sina Ghadermarzi, Bartosz Krawczyk, Jiangning Song, and 1 more author
    Bioinformatics, 2021
    HTML
  2. Self-adjusting k nearest neighbors for continual learning from multi-label drifting data streams
    Martha Roseberry, Bartosz Krawczyk, Youcef Djenouri, and 1 more author
    Neurocomputing, 2021
    HTML
  3. Multi-class imbalanced big data classification on Spark
    William C. Sleeman IV, and Bartosz Krawczyk
    Knowledge-Based Systems, 2021
    HTML
  4. Tensor decision trees for continual learning from drifting data streams
    Bartosz Krawczyk
    Machine Learning, 2021
    HTML
  5. On the combined effect of class imbalance and concept complexity in deep learning
    Kushankur Ghosh, Colin Bellinger, Roberto Corizzo, and 2 more authors
    In 2021 IEEE International Conference on Big Data (Big Data), Orlando, FL, USA, December 15-18, 2021, 2021
    HTML
  6. Class-Incremental Experience Replay for Continual Learning Under Concept Drift
    Lukasz Korycki, and Bartosz Krawczyk
    In IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2021, virtual, June 19-25, 2021, 2021
    HTML
  7. Concept Drift Detection from Multi-Class Imbalanced Data Streams
    Lukasz Korycki, and Bartosz Krawczyk
    In 37th IEEE International Conference on Data Engineering, ICDE 2021, Chania, Greece, April 19-22, 2021, 2021
    HTML
  8. Undersampling with Support Vectors for Multi-Class Imbalanced Data Classification
    Bartosz Krawczyk, Colin Bellinger, Roberto Corizzo, and 1 more author
    In International Joint Conference on Neural Networks, IJCNN 2021, Shenzhen, China, July 18-22, 2021, 2021
    HTML
  9. Evaluating and Explaining Generative Adversarial Networks for Continual Learning under Concept Drift
    Filip Guzy, Michal Wozniak, and Bartosz Krawczyk
    In 2021 International Conference on Data Mining, ICDM 2021 - Workshops, Auckland, New Zealand, December 7-10, 2021, 2021
    HTML
  10. Locally Linear Support Vector Machines for Imbalanced Data Classification
    Bartosz Krawczyk, and Alberto Cano
    In Advances in Knowledge Discovery and Data Mining - 25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11-14, 2021, Proceedings, Part I, 2021
    HTML
  11. Low-Dimensional Representation Learning from Imbalanced Data Streams
    Lukasz Korycki, and Bartosz Krawczyk
    In Advances in Knowledge Discovery and Data Mining - 25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11-14, 2021, Proceedings, Part I, 2021
    HTML
  12. Streaming Decision Trees for Lifelong Learning
    Lukasz Korycki, and Bartosz Krawczyk
    In Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings, Part I, 2021
    HTML

2020

  1. A Machine Learning method for relabeling arbitrary DICOM structure sets to TG-263 defined labels
    William C. Sleeman IV, Joseph Nalluri, Khajamoinuddin Syed, and 5 more authors
    Journal of Biomedical Informatics, 2020
    HTML
  2. Combined Cleaning and Resampling algorithm for multi-class imbalanced data with label noise
    Michal Koziarski, Michal Wozniak, and Bartosz Krawczyk
    Knowledge-Based Systems, 2020
    HTML
  3. Kappa Updated Ensemble for drifting data stream mining
    Alberto Cano, and Bartosz Krawczyk
    Machine Learning, 2020
    HTML
  4. Radial-Based Oversampling for Multiclass Imbalanced Data Classification
    Bartosz Krawczyk, Michal Koziarski, and Michal Wozniak
    IEEE Transactions on Neural Networks and Learning Systems, 2020
    HTML
  5. Online Oversampling for Sparsely Labeled Imbalanced and Non-Stationary Data Streams
    Lukasz Korycki, and Bartosz Krawczyk
    In 2020 International Joint Conference on Neural Networks, IJCNN 2020, Glasgow, United Kingdom, July 19-24, 2020, 2020
    HTML

2019

  1. Addressing the Overlapping Data Problem in Classification Using the One-vs-One Decomposition Strategy
    José A. Sáez, Mikel Galar, and Bartosz Krawczyk
    IEEE Access, 2019
    HTML
  2. Towards highly accurate coral texture images classification using deep convolutional neural networks and data augmentation
    Anabel Gómez-Rı́os, Siham Tabik, Julián Luengo, and 3 more authors
    Expert Systems with Applications, 2019
    HTML
  3. Monotonic classification: An overview on algorithms, performance measures and data sets
    José Ramón Cano, Pedro Antonio Gutiérrez, Bartosz Krawczyk, and 2 more authors
    Neurocomputing, 2019
    HTML
  4. Radial-Based oversampling for noisy imbalanced data classification
    Michal Koziarski, Bartosz Krawczyk, and Michal Wozniak
    Neurocomputing, 2019
    HTML
  5. Speeding up \emphk-Nearest Neighbors classifier for large-scale multi-label learning on GPUs
    Przemyslaw Skryjomski, Bartosz Krawczyk, and Alberto Cano
    Neurocomputing, 2019
    HTML
  6. Instance reduction for one-class classification
    Bartosz Krawczyk, Isaac Triguero, Salvador Garcı́a, and 2 more authors
    Knowledge and Information Systems, 2019
    HTML
  7. Evolving rule-based classifiers with genetic programming on GPUs for drifting data streams
    Alberto Cano, and Bartosz Krawczyk
    Pattern Recognition, 2019
    HTML
  8. Multi-Label Punitive kNN with Self-Adjusting Memory for Drifting Data Streams
    Martha Roseberry, Bartosz Krawczyk, and Alberto Cano
    ACM Transactions on Knowledge Discovery from Data, 2019
    HTML
  9. Active Learning with Abstaining Classifiers for Imbalanced Drifting Data Streams
    Lukasz Korycki, Alberto Cano, and Bartosz Krawczyk
    In 2019 IEEE International Conference on Big Data (IEEE BigData), Los Angeles, CA, USA, December 9-12, 2019, 2019
    HTML
  10. Bagging Using Instance-Level Difficulty for Multi-Class Imbalanced Big Data Classification on Spark
    William C. Sleeman IV, and Bartosz Krawczyk
    In 2019 IEEE International Conference on Big Data (IEEE BigData), Los Angeles, CA, USA, December 9-12, 2019, 2019
    HTML
  11. Unsupervised Drift Detector Ensembles for Data Stream Mining
    Lukasz Korycki, and Bartosz Krawczyk
    In 2019 IEEE International Conference on Data Science and Advanced Analytics, DSAA 2019, Washington, DC, USA, October 5-8, 2019, 2019
    HTML
  12. On the Role of Cost-Sensitive Learning in Imbalanced Data Oversampling
    Bartosz Krawczyk, and Michal Wozniak
    In Computational Science - ICCS 2019 - 19th International Conference, Faro, Portugal, June 12-14, 2019, Proceedings, Part III, 2019
    HTML
  13. Adaptive Ensemble Active Learning for Drifting Data Stream Mining
    Bartosz Krawczyk, and Alberto Cano
    In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI 2019, Macao, China, August 10-16, 2019, 2019
    HTML

2018

  1. Learning from Imbalanced Data Sets
    Alberto Fernández, Salvador Garcı́a, Mikel Galar, and 3 more authors
    2018
    HTML
  2. Online ensemble learning with abstaining classifiers for drifting and noisy data streams
    Bartosz Krawczyk, and Alberto Cano
    Applied Soft Computing, 2018
    HTML
  3. Ensemble of Extreme Learning Machines with trained classifier combination and statistical features for hyperspectral data
    Pawel Ksieniewicz, Bartosz Krawczyk, and Michal Wozniak
    Neurocomputing, 2018
    HTML
  4. Local ensemble learning from imbalanced and noisy data for word sense disambiguation
    Bartosz Krawczyk, and Bridget T. McInnes
    Pattern Recognition, 2018
    HTML
  5. Dynamic ensemble selection for multi-class classification with one-class classifiers
    Bartosz Krawczyk, Mikel Galar, Michal Wozniak, and 2 more authors
    Pattern Recognition, 2018
    HTML
  6. Clustering-Driven and Dynamically Diversified Ensemble for Drifting Data Streams
    Lukasz Korycki, and Bartosz Krawczyk
    In IEEE International Conference on Big Data (IEEE BigData 2018), Seattle, WA, USA, December 10-13, 2018, 2018
    HTML
  7. Combining active learning with concept drift detection for data stream mining
    Bartosz Krawczyk, Bernhard Pfahringer, and Michal Wozniak
    In IEEE International Conference on Big Data (IEEE BigData 2018), Seattle, WA, USA, December 10-13, 2018, 2018
    HTML
  8. Learning Classification Rules with Differential Evolution for High-Speed Data Stream Mining on GPU s
    Alberto Cano, and Bartosz Krawczyk
    In 2018 IEEE Congress on Evolutionary Computation, CEC 2018, Rio de Janeiro, Brazil, July 8-13, 2018, 2018
    HTML
  9. An Empirical Insight Into Concept Drift Detectors Ensemble Strategies
    Andrzej Lapinski, Bartosz Krawczyk, Pawel Ksieniewicz, and 1 more author
    In 2018 IEEE Congress on Evolutionary Computation, CEC 2018, Rio de Janeiro, Brazil, July 8-13, 2018, 2018
    HTML
  10. Addressing Local Class Imbalance in Balanced Datasets with Dynamic Impurity Decision Trees
    Andriy Mulyar, and Bartosz Krawczyk
    In Discovery Science - 21st International Conference, DS 2018, Limassol, Cyprus, October 29-31, 2018, Proceedings, 2018
    HTML
  11. Multi-class Imbalanced Data Oversampling for Vertebral Column Pathologies Classification
    José A. Sáez, Héctor Quintián, Bartosz Krawczyk, and 2 more authors
    In Hybrid Artificial Intelligent Systems - 13th International Conference, HAIS 2018, Oviedo, Spain, June 20-22, 2018, Proceedings, 2018
    HTML
  12. Synthetic Oversampling with the Majority Class: A New Perspective on Handling Extreme Imbalance
    Shiven Sharma, Colin Bellinger, Bartosz Krawczyk, and 2 more authors
    In IEEE International Conference on Data Mining, ICDM 2018, Singapore, November 17-20, 2018, 2018
    HTML
  13. Selecting local ensembles for multi-class imbalanced data classification
    Bartosz Krawczyk, Alberto Cano, and Michal Wozniak
    In 2018 International Joint Conference on Neural Networks, IJCNN 2018, Rio de Janeiro, Brazil, July 8-13, 2018, 2018
    HTML
  14. 2nd Workshop on Learning with Imbalanced Domains: Preface
    Luı́s Torgo, Stan Matwin, Nathalie Japkowicz, and 3 more authors
    In Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, LIDTA@ECML/PKDD 2018, Dublin, Ireland, September 10, 2018, 2018
    HTML
  15. Leveraging Ensemble Pruning for Imbalanced Data Classification
    Bartosz Krawczyk, and Michal Wozniak
    In IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018, Miyazaki, Japan, October 7-10, 2018, 2018
    HTML

2017

  1. Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble
    Jerzy Kowalski, Bartosz Krawczyk, and Michal Wozniak
    Engineering Applications of Artificial Intelligence, 2017
    HTML
  2. A survey on data preprocessing for data stream mining: Current status and future directions
    Sergio Ramı́rez-Gallego, Bartosz Krawczyk, Salvador Garcı́a, and 2 more authors
    Neurocomputing, 2017
    HTML
  3. Ensemble learning for data stream analysis: A survey
    Bartosz Krawczyk, Leandro L. Minku, João Gama, and 2 more authors
    Information Fusion, 2017
    HTML
  4. Active and adaptive ensemble learning for online activity recognition from data streams
    Bartosz Krawczyk
    Knowledge-Based Systems, 2017
    HTML
  5. Selecting locally specialised classifiers for one-class classification ensembles
    Bartosz Krawczyk, and Boguslaw Cyganek
    Pattern Analysis and Applications, 2017
    HTML
  6. The deterministic subspace method for constructing classifier ensembles
    Michal Koziarski, Bartosz Krawczyk, and Michal Wozniak
    Pattern Analysis and Applications, 2017
    HTML
  7. Nearest Neighbor Classification for High-Speed Big Data Streams Using Spark
    Sergio Ramı́rez-Gallego, Bartosz Krawczyk, Salvador Garcı́a, and 3 more authors
    IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017
    HTML
  8. Combining Active Learning and Self-Labeling for Data Stream Mining
    Lukasz Korycki, and Bartosz Krawczyk
    In Proceedings of the 10th International Conference on Computer Recognition Systems CORES 2017, Polanica Zdroj, Poland, 22-24 May 2017, 2017
    HTML
  9. Sentiment Classification from Multi-class Imbalanced Twitter Data Using Binarization
    Bartosz Krawczyk, Bridget T. McInnes, and Alberto Cano
    In Hybrid Artificial Intelligent Systems - 12th International Conference, HAIS 2017, La Rioja, Spain, June 21-23, 2017, Proceedings, 2017
    HTML
  10. Radial-Based Approach to Imbalanced Data Oversampling
    Michal Koziarski, Bartosz Krawczyk, and Michal Wozniak
    In Hybrid Artificial Intelligent Systems - 12th International Conference, HAIS 2017, La Rioja, Spain, June 21-23, 2017, Proceedings, 2017
    HTML
  11. Immersive browsing in an image sphere
    Gerald Schaefer, Mateusz Budnik, and Bartosz Krawczyk
    In Proceedings of the 11th International Conference on Ubiquitous Information Management and Communication, IMCOM 2017, Beppu, Japan, January 5-7, 2017, 2017
    HTML
  12. Online query by committee for active learning from drifting data streams
    Bartosz Krawczyk, and Michal Wozniak
    In 2017 International Joint Conference on Neural Networks, IJCNN 2017, Anchorage, AK, USA, May 14-19, 2017, 2017
    HTML
  13. Learning with Imbalanced Domains: Preface
    Luı́s Torgo, Bartosz Krawczyk, Paula Branco, and 1 more author
    In First International Workshop on Learning with Imbalanced Domains: Theory and Applications, LIDTA@PKDD/ECML 2017, 22 September 2017, Skopje, Macedonia, 2017
    HTML
  14. Influence of minority class instance types on SMOTE imbalanced data oversampling
    Przemyslaw Skryjomski, and Bartosz Krawczyk
    In First International Workshop on Learning with Imbalanced Domains: Theory and Applications, LIDTA@PKDD/ECML 2017, 22 September 2017, Skopje, Macedonia, 2017
    HTML
  15. Cost-Sensitive Perceptron Decision Trees for Imbalanced Drifting Data Streams
    Bartosz Krawczyk, and Przemyslaw Skryjomski
    In Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part II, 2017
    HTML

2016

  1. A Survey of Big Data Issues in Electronic Health Record Analysis
    Boguslaw Cyganek, Manuel Graña, Bartosz Krawczyk, and 4 more authors
    Appl. Artif. Intell., 2016
    HTML
  2. On the Influence of Class Noise in Medical Data Classification: Treatment Using Noise Filtering Methods
    José A. Sáez, Bartosz Krawczyk, and Michal Wozniak
    Appl. Artif. Intell., 2016
    HTML
  3. Evolutionary undersampling boosting for imbalanced classification of breast cancer malignancy
    Bartosz Krawczyk, Mikel Galar, Lukasz Jelen, and 1 more author
    Applied Soft Computing, 2016
    HTML
  4. Untrained weighted classifier combination with embedded ensemble pruning
    Bartosz Krawczyk, and Michal Wozniak
    Neurocomputing, 2016
    HTML
  5. Empowering one-vs-one decomposition with ensemble learning for multi-class imbalanced data
    Zhongliang Zhang, Bartosz Krawczyk, Salvador Garcı́a, and 2 more authors
    Knowledge-Based Systems, 2016
    HTML
  6. Dynamic classifier selection for one-class classification
    Bartosz Krawczyk, and Michal Wozniak
    Knowledge-Based Systems, 2016
    HTML
  7. Learning from imbalanced data: open challenges and future directions
    Bartosz Krawczyk
    Progress in Artificial Intelligence, 2016
    HTML
  8. Analyzing the oversampling of different classes and types of examples in multi-class imbalanced datasets
    José A. Sáez, Bartosz Krawczyk, and Michal Wozniak
    Pattern Recognition, 2016
    HTML
  9. Hybrid One-Class Ensemble for High-Dimensional Data Classification
    Bartosz Krawczyk
    In Intelligent Information and Database Systems - 8th Asian Conference, ACIIDS 2016, Da Nang, Vietnam, March 14-16, 2016, Proceedings, Part II, 2016
    HTML
  10. Ensemble of One-Dimensional Classifiers for Hyperspectral Image Analysis
    Pawel Ksieniewicz, Bartosz Krawczyk, and Michal Wozniak
    In Data Mining and Big Data, First International Conference, DMBD 2016, Bali, Indonesia, June 25-30, 2016. Proceedings, 2016
    HTML
  11. Forming Classifier Ensembles with Deterministic Feature Subspaces
    Michal Koziarski, Bartosz Krawczyk, and Michal Wozniak
    In Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, FedCSIS 2016, Gdańsk, Poland, September 11-14, 2016, 2016
    HTML
  12. Tackling label noise with multi-class decomposition using fuzzy one-class support vector machines
    Bartosz Krawczyk, José A. Sáez, and Michal Wozniak
    In 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016, Vancouver, BC, Canada, July 24-29, 2016, 2016
    HTML
  13. Workshop on Nonstationary Models of Pattern Recognition and Classifier Combinations
    Michal Wozniak, and Bartosz Krawczyk
    In International Conference on Computational Science 2016, ICCS 2016, 6-8 June 2016, San Diego, California, USA, 2016
    HTML
  14. GPU-Accelerated Extreme Learning Machines for Imbalanced Data Streams with Concept Drift
    Bartosz Krawczyk
    In International Conference on Computational Science 2016, ICCS 2016, 6-8 June 2016, San Diego, California, USA, 2016
    HTML
  15. Cost-sensitive one-vs-one ensemble for multi-class imbalanced data
    Bartosz Krawczyk
    In 2016 International Joint Conference on Neural Networks, IJCNN 2016, Vancouver, BC, Canada, July 24-29, 2016, 2016
    HTML

2015

  1. A hybrid cost-sensitive ensemble for imbalanced breast thermogram classification
    Bartosz Krawczyk, Gerald Schaefer, and Michal Wozniak
    Artificial Intelligence in Medicine, 2015
    HTML
  2. Multidimensional data classification with chordal distance based kernel and Support Vector Machines
    Boguslaw Cyganek, Bartosz Krawczyk, and Michal Wozniak
    Engineering Applications of Artificial Intelligence, 2015
    HTML
  3. Data stream classification and big data analytics
    Bartosz Krawczyk, Jerzy Stefanowski, and Michal Wozniak
    Neurocomputing, 2015
    HTML
  4. One-class classifier ensemble pruning and weighting with firefly algorithm
    Bartosz Krawczyk
    Neurocomputing, 2015
    HTML
  5. Incremental weighted one-class classifier for mining stationary data streams
    Bartosz Krawczyk, and Michal Wozniak
    Journal of Computational Science, 2015
    HTML
  6. Hybrid Ensemble Machine Learning for Complex and Dynamic Data
    Bartosz Krawczyk, and Bogdan Trawinski
    New Generation Computing, 2015
    HTML
  7. Forming Ensembles of Soft One-Class Classifiers with Weighted Bagging
    Bartosz Krawczyk
    New Generation Computing, 2015
    HTML
  8. On the usefulness of one-class classifier ensembles for decomposition of multi-class problems
    Bartosz Krawczyk, Michal Wozniak, and Francisco Herrera
    Pattern Recognition, 2015
    HTML
  9. One-class classifiers with incremental learning and forgetting for data streams with concept drift
    Bartosz Krawczyk, and Michal Wozniak
    Soft Computing, 2015
    HTML
  10. Pruning Ensembles of One-Class Classifiers with X-means Clustering
    Bartosz Krawczyk, and Michal Wozniak
    In Intelligent Information and Database Systems - 7th Asian Conference, ACIIDS 2015, Bali, Indonesia, March 23-25, 2015, Proceedings, Part I, 2015
    HTML
  11. Pruning Ensembles with Cost Constraints
    Bartosz Krawczyk, and Michal Wozniak
    In Intelligent Information and Database Systems - 7th Asian Conference, ACIIDS 2015, Bali, Indonesia, March 23-25, 2015, Proceedings, Part I, 2015
    HTML
  12. Data Classification with Ensembles of One-Class Support Vector Machines and Sparse Nonnegative Matrix Factorization
    Boguslaw Cyganek, and Bartosz Krawczyk
    In Intelligent Information and Database Systems - 7th Asian Conference, ACIIDS 2015, Bali, Indonesia, March 23-25, 2015, Proceedings, Part I, 2015
    HTML
  13. Combining One-vs-One Decomposition and Ensemble Learning for Multi-class Imbalanced Data
    Bartosz Krawczyk
    In Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015, Wroclaw, Poland, 25-27 May 2015, 2015
    HTML
  14. Reacting to different types of concept drift with adaptive and incremental one-class classifiers
    Bartosz Krawczyk, and Michal Wozniak
    In 2nd IEEE International Conference on Cybernetics, CYBCONF 2015, Gdynia, Poland, June 24-26, 2015, 2015
    HTML
  15. Combining nearest neighbour classifiers based on small subsamples for big data analytics
    Bartosz Krawczyk, and Michal Wozniak
    In 2nd IEEE International Conference on Cybernetics, CYBCONF 2015, Gdynia, Poland, June 24-26, 2015, 2015
    HTML
  16. Wagging for Combining Weighted One-class Support Vector Machines
    Bartosz Krawczyk, and Michal Wozniak
    In Proceedings of the International Conference on Computational Science, ICCS 2015, Computational Science at the Gates of Nature, Reykjavı́k, Iceland, 1-3 June, 2015, 2014, 2015
    HTML
  17. Cost-Sensitive Neural Network with ROC-Based Moving Threshold for Imbalanced Classification
    Bartosz Krawczyk, and Michal Wozniak
    In Intelligent Data Engineering and Automated Learning - IDEAL 2015 - 16th International Conference Wroclaw, Poland, October 14-16, 2015, Proceedings, 2015
    HTML
  18. Effective Imbalanced Classification of Breast Thermogram Features
    Bartosz Krawczyk, and Gerald Schaefer
    In Pattern Recognition and Machine Intelligence - 6th International Conference, PReMI 2015, Warsaw, Poland, June 30 - July 3, 2015, Proceedings, 2015
    HTML
  19. Weighted Naı̈ve Bayes Classifier with Forgetting for Drifting Data Streams
    Bartosz Krawczyk, and Michal Wozniak
    In 2015 IEEE International Conference on Systems, Man, and Cybernetics, Kowloon Tong, Hong Kong, October 9-12, 2015, 2015
    HTML
  20. Incremental One-Class Bagging for Streaming and Evolving Big Data
    Bartosz Krawczyk, and Michal Wozniak
    In 2015 IEEE TrustCom/BigDataSE/ISPA, Helsinki, Finland, August 20-22, 2015, Volume 2, 2015
    HTML

2014

  1. Recent Advances in Applied Computational Intelligence
    Bartosz Krawczyk, Urszula Markowska-Kaczmar, and Halina Kwasnicka
    Applied Artificial Intelligence, 2014
    HTML
  2. Influence of Distance Measures on the Effectiveness of One-Class Classification Ensembles
    Bartosz Krawczyk, and Michal Wozniak
    Applied Artificial Intelligence, 2014
    HTML
  3. Cost-sensitive decision tree ensembles for effective imbalanced classification
    Bartosz Krawczyk, Michal Wozniak, and Gerald Schaefer
    Applied Soft Computing, 2014
    HTML
  4. A hybrid classifier committee for analysing asymmetry features in breast thermograms
    Bartosz Krawczyk, and Gerald Schaefer
    Applied Soft Computing, 2014
    HTML
  5. Cytological image analysis with firefly nuclei detection and hybrid one-class classification decomposition
    Bartosz Krawczyk, and Pawel Filipczuk
    Engineering Applications of Artificial Intelligence, 2014
    HTML
  6. Improved Adaptive Splitting and Selection: the Hybrid Training Method of a Classifier Based on a Feature Space Partitioning
    Konrad Jackowski, Bartosz Krawczyk, and Michal Wozniak
    International Journal of Neural Systems, 2014
    HTML
  7. Diversity measures for one-class classifier ensembles
    Bartosz Krawczyk, and Michal Wozniak
    Neurocomputing, 2014
    HTML
  8. Clustering-based ensembles for one-class classification
    Bartosz Krawczyk, Michal Wozniak, and Boguslaw Cyganek
    Information Sciences, 2014
    HTML
  9. An ensemble classification approach for melanoma diagnosis
    Gerald Schaefer, Bartosz Krawczyk, M. Emre Celebi, and 1 more author
    Memetic Computing, 2014
    HTML
  10. Breast Thermogram Analysis Using Classifier Ensembles and Image Symmetry Features
    Bartosz Krawczyk, and Gerald Schaefer
    IEEE Systems Journal, 2014
    HTML
  11. Optimization Algorithms for One-Class Classification Ensemble Pruning
    Bartosz Krawczyk, and Michal Wozniak
    In Intelligent Information and Database Systems - 6th Asian Conference, ACIIDS 2014, Bangkok, Thailand, April 7-9, 2014, Proceedings, Part II, 2014
    HTML
  12. Melanoma Classification Based on Ensemble Classification of Dermoscopy Image Features
    Gerald Schaefer, Bartosz Krawczyk, M. Emre Celebi, and 2 more authors
    In Advanced Machine Learning Technologies and Applications - Second International Conference, AMLTA 2014, Cairo, Egypt, November 28-30, 2014. Proceedings, 2014
    HTML
  13. Cost-sensitive texture classification
    Gerald Schaefer, Bartosz Krawczyk, Niraj P. Doshi, and 1 more author
    In Proceedings of the IEEE Congress on Evolutionary Computation, CEC 2014, Beijing, China, July 6-11, 2014, 2014
    HTML
  14. A first attempt on evolutionary prototype reduction for nearest neighbor one-class classification
    Bartosz Krawczyk, Isaac Triguero, Salvador Garcı́a, and 2 more authors
    In Proceedings of the IEEE Congress on Evolutionary Computation, CEC 2014, Beijing, China, July 6-11, 2014, 2014
    HTML
  15. Adaptive Splitting and Selection ensemble for breast cancer malignancy grading
    Bartosz Krawczyk, Lukasz Jelen, and Michal Wozniak
    In 2014 IEEE Symposium on Computational Intelligence in Healthcare and e-health, CICARE 2014, Orlando, FL, USA, December 9-12, 2014, 2014
    HTML
  16. Weighted one-class classification for different types of minority class examples in imbalanced data
    Bartosz Krawczyk, Michal Wozniak, and Francisco Herrera
    In 2014 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2014, Orlando, FL, USA, December 9-12, 2014, 2014
    HTML
  17. Experiments on simultaneous combination rule training and ensemble pruning algorithm
    Bartosz Krawczyk, and Michal Wozniak
    In 2014 IEEE Symposium on Computational Intelligence in Ensemble Learning, CIEL 2014, Orlando, FL, USA, December 9-12, 2014, 2014
    HTML
  18. Designing a compact Genetic fuzzy rule-based system for one-class classification
    Pedro Villar, Bartosz Krawczyk, Ana M. Sánchez, and 2 more authors
    In IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2014, Beijing, China, July 6-11, 2014, 2014
    HTML
  19. Hyperspectral Image Analysis Based on Color Channels and Ensemble Classifier
    Bartosz Krawczyk, Pawel Ksieniewicz, and Michal Wozniak
    In Hybrid Artificial Intelligence Systems - 9th International Conference, HAIS 2014, Salamanca, Spain, June 11-13, 2014. Proceedings, 2014
    HTML
  20. Clustering-Based Ensemble of One-Class Classifiers for Hyperspectral Image Segmentation
    Bartosz Krawczyk, Michal Wozniak, and Boguslaw Cyganek
    In Hybrid Artificial Intelligence Systems - 9th International Conference, HAIS 2014, Salamanca, Spain, June 11-13, 2014. Proceedings, 2014
    HTML
  21. One-Class Classification Decomposition for Imbalanced Classification of Breast Cancer Malignancy Data
    Bartosz Krawczyk, Lukasz Jelen, Adam Krzyzak, and 1 more author
    In Artificial Intelligence and Soft Computing - 13th International Conference, ICAISC 2014, Zakopane, Poland, June 1-5, 2014, Proceedings, Part I, 2014
    HTML
  22. Weighted One-Class Classifier Ensemble Based on Fuzzy Feature Space Partitioning
    Bartosz Krawczyk, Michal Wozniak, and Boguslaw Cyganek
    In 22nd International Conference on Pattern Recognition, ICPR 2014, Stockholm, Sweden, August 24-28, 2014, 2014
    HTML
  23. Hypertension Type Classification Using Hierarchical Ensemble of One-Class Classifiers for Imbalanced Data
    Bartosz Krawczyk, and Michal Wozniak
    In ICT Innovations 2014 - World of Data, Ohrid, Macedonia, 1-4 October, 2014, 2014
    HTML
  24. Handling Label Noise in Microarray Classification with One-Class Classifier Ensemble
    Bartosz Krawczyk, and Michal Wozniak
    In ICT Innovations 2014 - World of Data, Ohrid, Macedonia, 1-4 October, 2014, 2014
    HTML
  25. New untrained aggregation methods for classifier combination
    Bartosz Krawczyk, and Michal Wozniak
    In 2014 International Joint Conference on Neural Networks, IJCNN 2014, Beijing, China, July 6-11, 2014, 2014
    HTML
  26. Untrained Method for Ensemble Pruning and Weighted Combination
    Bartosz Krawczyk, and Michal Wozniak
    In Advances in Neural Networks - ISNN 2014 - 11th International Symposium on Neural Networks, ISNN 2014, Hong Kong and Macao, China, November 28- December 1, 2014. Proceedings, 2014
    HTML
  27. One-Class Classification Ensemble with Dynamic Classifier Selection
    Bartosz Krawczyk, and Michal Wozniak
    In Advances in Neural Networks - ISNN 2014 - 11th International Symposium on Neural Networks, ISNN 2014, Hong Kong and Macao, China, November 28- December 1, 2014. Proceedings, 2014
    HTML
  28. 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, and 1 more author
    In International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2014, Granada, Spain, April 7-9, 2014, 2014
    HTML
  29. Hyperspectral Image Analysis Based on Quad Tree Decomposition
    Bartosz Krawczyk, Pawel Ksieniewicz, and Michal Wozniak
    In International Joint Conference SOCO’14-CISIS’14-ICEUTE’14 - Bilbao, Spain, June 25th-27th, 2014, Proceedings, 2014
    HTML
  30. Evolutionary Cost-Sensitive Ensemble for Malware Detection
    Bartosz Krawczyk, and Michal Wozniak
    In International Joint Conference SOCO’14-CISIS’14-ICEUTE’14 - Bilbao, Spain, June 25th-27th, 2014, Proceedings, 2014
    HTML

2013

  1. Application of Adaptive Splitting and Selection Classifier to the Spam Filtering Problem
    Konrad Jackowski, Bartosz Krawczyk, and Michal Wozniak
    Cybernetics and Systems, 2013
    HTML
  2. On optimal settings of classification tree ensembles for medical decision support
    Mateusz Budnik, and Bartosz Krawczyk
    Health Informatics Journal, 2013
    HTML
  3. Classifier ensemble for an effective cytological image analysis
    Pawel Filipczuk, Bartosz Krawczyk, and Michal Wozniak
    Pattern Recognition Letters, 2013
    HTML

2012

    2011