Mykola Pechenizkiy
Cited by
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A survey on concept drift adaptation
J Gama, I Žliobaitė, A Bifet, M Pechenizkiy, A Bouchachia
ACM computing surveys (CSUR) 46 (4), 1-37, 2014
Handbook of educational data mining
C Romero, S Ventura, M Pechenizkiy, RSJ Baker
CRC press, 2010
Predicting students drop out: A case study
GW Dekker, M Pechenizkiy, JM Vleeshouwers
Proceedings of the 2nd International Conference on Educational Data Mining …, 2009
Building classifiers with independency constraints
T Calders, F Kamiran, M Pechenizkiy
2009 IEEE international conference on data mining workshops, 13-18, 2009
An overview of concept drift applications
I Žliobaitė, M Pechenizkiy, J Gama
Big data analysis: new algorithms for a new society, 91-114, 2016
Discrimination aware decision tree learning
F Kamiran, T Calders, M Pechenizkiy
ICDM 2010: IEEE International Conference on Data Mining, 869-874, 2010
Diversity in search strategies for ensemble feature selection
A Tsymbal, M Pechenizkiy, P Cunningham
Information fusion 6 (1), 83-98, 2005
What's your current stress level? Detection of stress patterns from GSR sensor data
J Bakker, M Pechenizkiy, N Sidorova
2011 IEEE 11th international conference on data mining workshops, 573-580, 2011
Dynamic integration of classifiers for handling concept drift
A Tsymbal, M Pechenizkiy, P Cunningham, S Puuronen
Information fusion 9 (1), 56-68, 2008
Stress detection from speech and galvanic skin response signals
H Kurniawan, AV Maslov, M Pechenizkiy
CBMS 2013: Proceedings of the 26th IEEE international symposium on computer …, 2013
AH 12 years later: a comprehensive survey of adaptive hypermedia methods and techniques
E Knutov, P De Bra, M Pechenizkiy
New review of hypermedia and multimedia 15 (1), 5-38, 2009
Handling concept drift in process mining
RPJC Bose, WMP van der Aalst, I Žliobaitė, M Pechenizkiy
Advanced Information Systems Engineering: 23rd International Conference …, 2011
On formalizing fairness in prediction with machine learning
P Gajane, M Pechenizkiy
arXiv preprint arXiv:1710.03184, 2017
Feedback loop and bias amplification in recommender systems
M Mansoury, H Abdollahpouri, M Pechenizkiy, B Mobasher, R Burke
CIKM 2020: Proceedings of the 29th ACM international conference on …, 2020
Dealing with concept drifts in process mining
RPJC Bose, WMP Van Der Aalst, I Žliobaitė, M Pechenizkiy
IEEE transactions on neural networks and learning systems 25 (1), 154-171, 2013
Graph-based n-gram language identification on short texts
E Tromp, M Pechenizkiy
Proc. 20th Machine Learning conference of Belgium and The Netherlands, 27-34, 2011
Introduction to the special section on educational data mining
T Calders, M Pechenizkiy
Acm Sigkdd Explorations Newsletter 13 (2), 3-6, 2012
More convnets in the 2020s: Scaling up kernels beyond 51x51 using sparsity
S Liu, T Chen, X Chen, X Chen, Q Xiao, B Wu, T Karkkainen, ...
ICLR 2023 preprint arXiv:2207.03620, 2023
Class noise and supervised learning in medical domains: The effect of feature extraction
M Pechenizkiy, A Tsymbal, S Puuronen, O Pechenizkiy
CBMS 2006: 19th IEEE Symposium on Computer-Based Medical Systems, 708-713, 2006
Process mining from educational data
N Trcˇka, M Pechenizkiy, W van der Aalst
Handbook of educational data mining, 123-142, 2011
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