Maciej Zieba
Maciej Zieba
Wroclaw University of Technology, Tooploox
Verified email at - Homepage
TitleCited byYear
Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction
M Zięba, SK Tomczak, JM Tomczak
Expert Systems with Applications 58, 93-101, 2016
Boosted SVM for extracting rules from imbalanced data in application to prediction of the post-operative life expectancy in the lung cancer patients
M Zięba, JM Tomczak, M Lubicz, J Świątek
Applied soft computing 14, 99-108, 2014
Classification restricted Boltzmann machine for comprehensible credit scoring model
JM Tomczak, M Zięba
Expert Systems with Applications 42 (4), 1789-1796, 2015
Boosted SVM with active learning strategy for imbalanced data
M Zięba, JM Tomczak
Soft Computing 19 (12), 3357-3368, 2015
Probabilistic combination of classification rules and its application to medical diagnosis
JM Tomczak, M ZięBa
Machine Learning 101 (1-3), 105-135, 2015
Service-oriented medical system for supporting decisions with missing and imbalanced data
M Zięba
IEEE journal of biomedical and health informatics 18 (5), 1533-1540, 2014
The proposal of service oriented data mining system for solving real-life classification and regression problems
A Prusiewicz, M Zięba
Doctoral Conference on Computing, Electrical and Industrial Systems, 83-90, 2011
Services Recommendation in Systems Based on Service Oriented Architecture by Applying Modified ROCK Algorithm
A Prusiewicz, M Zieba
Networked Digital Technologies - Second International Conference, NDT 2010 …, 2010
Bingan: Learning compact binary descriptors with a regularized gan
M Zieba, P Semberecki, T El-Gaaly, T Trzcinski
Advances in Neural Information Processing Systems, 3608-3618, 2018
Ensemble classifier for solving credit scoring problems
M Zięba, J Świątek
Doctoral Conference on Computing, Electrical and Industrial Systems, 59-66, 2012
Training triplet networks with gan
M Zieba, L Wang
arXiv preprint arXiv:1704.02227, 2017
RBM-SMOTE: restricted Boltzmann machines for synthetic minority oversampling technique
M Zięba, JM Tomczak, A Gonczarek
Asian Conference on Intelligent Information and Database Systems, 377-386, 2015
NMRNet: a deep learning approach to automated peak picking of protein NMR spectra
P Klukowski, M Augoff, M Zięba, M Drwal, A Gonczarek, MJ Walczak
Bioinformatics 34 (15), 2590-2597, 2018
Analysis of human arm motions recognition algorithms for system to visualize virtual arm
K Brzostowski, M Zieba
2011 21st International Conference on Systems Engineering, 422-426, 2011
Adversarial Autoencoders for Compact Representations of 3D Point Clouds
M Zamorski, M Zięba, P Klukowski, R Nowak, K Kurach, W Stokowiec, ...
arXiv preprint arXiv:1811.07605, 2018
On-line bayesian context change detection in web service systems
JM Tomczak, M Zieba
Proceedings of the 2013 international workshop on Hot topics in cloud …, 2013
On some method for limited services selection
A Prusiewicz, M Zieba
International Journal of Intelligent Information and Database Systems 5 (5 …, 2011
Gaussian process regression for automated signal tracking in step-wise perturbed Nuclear Magnetic Resonance spectra
M Zieba, P Klukowski, A Gonczarek, Y Nikolaev, MJ Walczak
Applied Soft Computing 68, 162-171, 2018
Beta-boosted ensemble for big credit scoring data
M Zieba, WK Härdle
Handbook of Big Data Analytics, 523-538, 2018
Analiza porów-nawcza wybranych technik eksploracji danych do klasyfikacji danych medycznych z brakującymi obserwacjami
M Lubicz, M Zięba, A Rzechonek, K Pawełczyk, J Kołodziej, J Błaszczyk
Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu, 416-425, 2012
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