prof. dr hab. inż.

Michał Woźniak


info Consultation hours: Mo 11a.m.-1p.m, We 11a.m.-1p.m.

Prowadzi w tym semestrze
Methods of computational
Uczenie maszyn

See movie about Poland** https://youtu.be/YCelkqmkxMs
In 2019 we will organize conference on computer recogition systems CORES** http://cores.pwr.edu.pl/ - join us!
Fields of interest
  • machine learning,
  • data stream mining,
  • data stream classification, concept drift,
  • ensemble learning, classifier ensemble
  • inductive learning, data and web mining,
  • learning on distributed and streaming data
  • pattern classification,
  • imabalance data classification,
  • classification with recognition with context
  • telemedicine and medical decision support

Google Scholar profile
ORCID
ResearchGate profile
ResearchID profile
List of publication in DONA database - maintained by my University

New publications
  1. Bartosz Krawczyk, Isaac Triguero Salvador García, Michał Woźniak, Francisco Herrera, Instance reduction for one-class classification, Knowledge and Information Systems
  2. Bartosz Krawczyk, Mikel Galar, Michał Woźniak, Humberto Bustince, Francisco Herrera, Dynamic Ensemble Selection for Multi-Class Classification with One-Class Classifiers, Pattern Recognition 83 (2018) 34–51.
  3. Pawe Ksieniewicz, Micha Woźniak, Bogusaw Cyganek, Andrzej Kasprzak, Krzysztof Walkowiak, Data Stream Classification using Active Learned Neural Networks, Neurocomputing (ACCEPTED)
  4. Michał Koziarski, Bartosz Krawczyk, Michał Wożniak, Radial-Based Oversampling for Noisy Imbalanced Data Classification, Neurocomputing (ACCEPTED)
  5. Bogusław Cyganek, Michał Wozniak, Extended Ensemble of Tensor Subspace Based Classifiers with Optimized Flattening Directions, Neurocomputing (ACCEPTED)
  6. Andrzej Łapiński, Bartosz Krawczyk, Paweł Ksieniewicz, Michał Woźniak, Different Strategies of Concept Drift Detector Ensemble Forming - Experimental Study, WCCI 2018 (ACCEPTED)
  7. Bartosz Krawczyk, Alberto Cano, Michał Woźniak, Selecting local ensembles for multi-class imbalanced data classification, WCCI 2018 (ACCEPTED)
  8. Jakub Zgraja, Michał Woźniak, Drifted Data Stream Clustering Based on ClusTree Algorithm, HAIS 2018 (ACCEPTED)
  9. Jose A. Saez, Hector Quintian, Bartosz Krawczyk, Michał Woźniak,Emilio Corchado, Multi-class imbalanced data oversampling for vertebral column pathologies classification, HAIS 2018 (ACCEPTED)
  10. Barbara Bobowska, Michał Choraś, Michał Woźniak, Advanced Analysis of Data Streams for Critical Infrastructures Protection and Cybersecurity, Journal of Universal Computer Science (ACCEPTED)
  11. Barbara Bobowska, Michał Woźniak, Experimental study on Modified Radial-Based Oversampling, SOCO 2018

today
Rozkład zajęć

Poniedziałek

methods of computational
C-4: 40 9.15- 11.00
uczenie maszyn
C-3: 114 15.15- 16.55
uczenie maszyn
C-4: 40 9.15- 11.00
uczenie maszyn
C-3: 114 15.15- 16.55
11.00
|
13.00

Wtorek

Środa

uczenie maszyn
C-4: 40 9.15- 11.00
uczenie maszyn
C-3: 114 13.15- 15.00
uczenie maszyn
C-3: 114 15.15- 16.55
11.00
|
13.00

Czwartek

Piątek


local_library
Zainteresowania badawcze

bookmark
Wybrane publikacje
Książki
Artykuły w czasopismach
Andrzej.kasprzak Andrzej Kasprzak
Walkowiak 2015 Krzysztof Walkowiak
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
+3
A Survey of big data issues in electronic health record analysis 
in APPLIED ARTIFICIAL INTELLIGENCE, 2016
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
+3
Ensemble learning for data stream analysis: A survey 
in Information Fusion, 2017
Pawel ksieniewicz Paweł Ksieniewicz
Mw einstein Michał Woźniak
+1
Paired feature multilayer ensemble – concept and evaluation of a classifier 
in Journal of Intelligent & Fuzzy Systems, 2017
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
+1
Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble 
in Engineering Applications of Artificial Intelligence, 2017
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
+3
A survey on data preprocessing for data stream mining : current status and future directions 
in Neurocomputing, 2017
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
+1
A hybrid cost-sensitive ensemble for imbalanced breast thermogram classification 
in ARTIFICIAL INTELLIGENCE IN MEDICINE, 2015
Pawel ksieniewicz Paweł Ksieniewicz
Dariusz.jankowski Dariusz Jankowski
Mw einstein Michał Woźniak
Konrad.jackowski Konrad Jackowski
+2
A novel hyperspectral segmentation algorithm - concept and evaluation 
in LOGIC JOURNAL OF THE IGPL, 2015
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
Influence of distance measures on the effectiveness of one-class classification ensembles 
in APPLIED ARTIFICIAL INTELLIGENCE, 2014
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
+1
Classifier ensemble for an effective cytological image analysis 
in PATTERN RECOGNITION LETTERS, 2013
Mw einstein Michał Woźniak
+2
A survey of multiple classifier systems as hybrid systems 
in Information Fusion, 2014
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
+1
On the influence of class noise in medical data classification: treatment using noise filtering methods 
in APPLIED ARTIFICIAL INTELLIGENCE, 2016
Mw einstein Michał Woźniak
+3
A new heuristic for influence maximization in social networks 
in Logic Journal of the IGPL, 2016
Mw einstein Michał Woźniak
Piotr.sobolewski Piotr Sobolewski
SCR: simulated concept recurrence - a non-supervised tool for dealing with shifting concept 
in EXPERT SYSTEMS, 2013
Mw einstein Michał Woźniak
Piotr.sobolewski Piotr Sobolewski
Concept drift detection and model selection with simulated recurrence and ensembles of statistical detectors 
in JOURNAL OF UNIVERSAL COMPUTER SCIENCE, 2013
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
Dynamic classifier selection for one-class classification 
in KNOWLEDGE-BASED SYSTEMS, 2016
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
Untrained weighted classifier combination with embedded ensemble pruning 
in NEUROCOMPUTING, 2016
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
+1
Analyzing the oversampling of different classes and types of examples in multi-class imbalanced datasets 
in PATTERN RECOGNITION, 2016
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
Diversity measures for one-class classifier ensembles 
in NEUROCOMPUTING, 2014
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
Konrad.jackowski Konrad Jackowski
Application of adaptive splitting and selection classifier to the SPAM filtering problem 
in CYBERNETICS AND SYSTEMS, 2013
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
+1
Cost-sensitive decision tree ensembles for effective imbalanced classification 
in APPLIED SOFT COMPUTING, 2014
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
+2
Diversity-based classifier selection for breast cancer cytological image analysis 
in BIOMEDICAL ENGINEERING-APPLICATIONS BASIS COMMUNICATIONS, 2013
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
+1
Clustering-based ensembles for one-class classification 
in INFORMATION SCIENCES, 2014
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
Konrad.jackowski Konrad Jackowski
Improved adaptive splitting and selection: the hybrid training method of a classifier based on a feature space partitioning 
in International Journal of Neural Systems, 2014
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
+1
On the usefulness of one-class classifier ensembles for decomposition of multi-class problems 
in PATTERN RECOGNITION, 2015
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
One-class classifiers with incremental learning and forgetting for data streams with concept drift 
in SOFT COMPUTING, 2015
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
Incremental weighted one-class classifier for mining stationary data streams 
in Journal of Computational Science, 2015
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
+1
Multidimensional data classification with chordal distance based kernel and support vector machines 
in ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2015
Mw einstein Michał Woźniak
+1
An improved vehicle logo recognition using a classifier ensemble based on pattern tensor representation and decomposition 
in NEW GENERATION COMPUTING, 2015
Publikacje konferencyjne
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
Łukasz Jeleń
Adaptive splitting and selection ensemble for breast cancer malignancy grading 
2014 IEEE Symposium Series on Computational Intelligence : IEEE SSCI 2014 : 2014 IEEE Symposium on Computational Intelligence in Healthcare and e-health, CICARE 2014 : proceedings, December 9-12, 2014, Orlando, Florida, USA
Missing Michał Koziarski
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
Radial-based approach to imbalanced data oversampling 
Hybrid Artificial Intelligent Systems : 12th International Conference, HAIS 2017, La Rioja, Spain, June 21-23, 2017 : proceedings
Mw einstein Michał Woźniak
+1
Efficient real-time background detection based on the PCA subspace decomposition 
Artificial intelligence and soft computing : 16th International Conference, ICAISC 2017, Zakopane, Poland, June 11-15, 2017 : proceedings. Pt. 1
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
Online query by committee for active learning from drifting data streams 
IJCNN 2017 : The International Joint Conference on Neural Networks : May 14-19, 2017, Anchorage, Alaska, USA
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
+1
Tackling Label Noise with Multi-Class Decomposition using Fuzzy One-Class Support Vector Machines 
2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 24-29 July 2016, Vancouver, Canada
Missing Michał Koziarski
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
Forming classifier ensembles with deterministic feature subspaces 
Proceedings of the 2016 Federated Conference on Computer Science and Information Systems : September 11–14, 2016, Gdańsk, Poland
Mw einstein Michał Woźniak
Piotr.sobolewski Piotr Sobolewski
LDCnet: minimizing the cost of supervision for various types of concept drift 
Proceedings of the 2013 IEEE Symposium Series on Computational Intelligence (SSCI) : 2013 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments (CIDUE), 16-19 April 2013, Singapore
Mw einstein Michał Woźniak
Piotr.sobolewski Piotr Sobolewski
Comparable study of statistical tests for virtual concept drift detection 
Proceedings of the 8th International Conference on Computer Recognition Systems : CORES 2013
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
Mining imbalanced medical streams for automated fetal state assesment 
4th Workshop on Machine Learning in Life Sciences (MLLS), 23 September 2016, Riva del Garda, Italy, 23 September 2016 : proceedings
Pawel ksieniewicz Paweł Ksieniewicz
Mw einstein Michał Woźniak
Imbalance medical data classification using exposer classifier ensemble 
4th Workshop on Machine Learning in Life Sciences (MLLS), 23 September 2016, Riva del Garda, Italy, 23 September 2016 : proceedings
Pawel ksieniewicz Paweł Ksieniewicz
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
Ensemble of one-dimensional classifiers for hyperspectral image analysis 
Data Mining and Big Data : First International Conference, DMBD 2016, Bali, Indonesia, June 25-30, 2016 : proceedings
Andrzej.kasprzak Andrzej Kasprzak
Aaeaaqaaaaaaaaq7aaaajdg5y2fingi0lwvkzgutndizyy1inzi4ltdlzjflnge0njrhzg Piotr Cal
Mw einstein Michał Woźniak
Weighted aging classifier ensemble for the incremental drifted data streams 
Flexible Query Answering Systems : 10th International Conference, FQAS 2013, Granada, Spain, September 18-20, 2013 : proceedings
Andrzej.kasprzak Andrzej Kasprzak
Walkowiak 2015 Krzysztof Walkowiak
Pawel ksieniewicz Paweł Ksieniewicz
Mw einstein Michał Woźniak
+1
Active learning clasiffier for streaming data 
Hybrid artificial intelligent systems : 11th International Conference, HAIS 2016, Seville, Spain, April 18-20, 2016 : proceedings
Pawel ksieniewicz Paweł Ksieniewicz
Ja 2017 Bartosz Krawczyk
Mw einstein Michał Woźniak
Hyperspectral image analysis based on color channels and ensemble classifier 
Hybrid artificial intelligence systems : 9th international conference, HAIS 2014, Salamanca, Spain, June 11-13, 2014 : proceedings
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