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ORCIDTomasz S. Zabkowski
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Journal Articles
- 2024
[j11]Krzysztof Gajowniczek
, Tomasz S. Zabkowski, Artur Krupa, Wieslaw Szczesny:
GradeStat: An R package for grade correspondence analysis. SoftwareX 27: 101790 (2024)- 2021
- [j10]Krzysztof Gajowniczek, Tomasz S. Zabkowski:
ImbTreeAUC: An R package for building classification trees using the area under the ROC curve (AUC) on imbalanced datasets. SoftwareX 15: 100755 (2021) - [j9]Krzysztof Gajowniczek, Tomasz S. Zabkowski:
ImbTreeEntropy: An R package for building entropy-based classification trees on imbalanced datasets. SoftwareX 16: 100841 (2021) - 2020
- [j8]Krzysztof Gajowniczek, Yitao Liang, Tal Friedman, Tomasz S. Zabkowski, Guy Van den Broeck:
Semantic and Generalized Entropy Loss Functions for Semi-Supervised Deep Learning. Entropy 22(3): 334 (2020) - [j7]Krzysztof Gajowniczek, Marcin Bator, Tomasz S. Zabkowski:
Whole Time Series Data Streams Clustering: Dynamic Profiling of the Electricity Consumption. Entropy 22(12): 1414 (2020) - 2019
- [j6]Krzysztof Gajowniczek, Iga Grzegorczyk, Tomasz S. Zabkowski:
Reducing False Arrhythmia Alarms Using Different Methods of Probability and Class Assignment in Random Forest Learning Methods. Sensors 19(7): 1588 (2019) - 2018
- [j5]Krzysztof Gajowniczek, Tomasz S. Zabkowski:
Simulation Study on Clustering Approaches for Short-Term Electricity Forecasting. Complex. 2018: 3683969:1-3683969:21 (2018) - [j4]Krzysztof Gajowniczek, Arkadiusz Orlowski, Tomasz S. Zabkowski:
Simulation Study on the Application of the Generalized Entropy Concept in Artificial Neural Networks. Entropy 20(4): 249 (2018) - 2016
- [j3]Krzysztof Gajowniczek, Tomasz S. Zabkowski:
Short term electricity forecasting based on user behavior from individual smart meter data. J. Intell. Fuzzy Syst. 30(1): 223-234 (2016) - [j2]Tomasz S. Zabkowski:
RFM approach for telecom insolvency modeling. Kybernetes 45(5): 815-827 (2016) - 2012
- [j1]Tomasz S. Zabkowski, Wieslaw Szczesny:
Insolvency modeling in the cellular telecommunication industry. Expert Syst. Appl. 39(8): 6879-6886 (2012)
Conference and Workshop Papers
- 2022
- [c30]Malgorzata Charytanowicz, Anna Olwert, Weronika Radziszewska, Jolanta Jarnicka, Krzysztof Gajowniczek, Tomasz S. Zabkowski, Jacek Brozyna, Grzegorz Mentel, Grzegorz Matejko:
Machine Learning for Energy Load Prediction and its Interpretation. IS 2022: 1-8 - 2021
- [c29]Rafik Nafkha, Tomasz S. Zabkowski, Krzysztof Gajowniczek:
Two Stage Approach to Optimize Electricity Contract Capacity Problem for Commercial Customers. ICCS (4) 2021: 173-184 - 2020
- [c28]Krzysztof Gajowniczek, Tomasz S. Zabkowski:
Generalized Entropy Loss Function in Neural Network: Variable's Importance and Sensitivity Analysis. EANN 2020: 535-545 - 2017
- [c27]Krzysztof Gajowniczek, Rafik Nafkha, Tomasz S. Zabkowski:
Electricity peak demand classification with artificial neural networks. FedCSIS 2017: 307-315 - [c26]Krzysztof Gajowniczek, Leszek J. Chmielewski, Arkadiusz Orlowski, Tomasz S. Zabkowski:
Generalized Entropy Cost Function in Neural Networks. ICANN (2) 2017: 128-136 - [c25]Tomasz S. Zabkowski, Krzysztof Gajowniczek:
Grade Analysis for households segmentation based on energy usage patterns. INISTA 2017: 168-173 - 2015
- [c24]Krzysztof Gajowniczek, Tomasz S. Zabkowski, Ryszard Szupiluk:
Blind Source Separation for Improved Load Forecasting on Individual Household Level. CORES 2015: 181-190 - [c23]Tomasz S. Zabkowski, Krzysztof Gajowniczek, Ryszard Szupiluk:
Grade analysis for energy usage patterns segmentation based on smart meter data. CYBCONF 2015: 234-239 - [c22]Krzysztof Gajowniczek, Tomasz S. Zabkowski, Arkadiusz Orlowski:
Comparison of decision trees with Rényi and Tsallis entropy applied for imbalanced churn dataset. FedCSIS 2015: 39-44 - [c21]Ryszard Szupiluk, Tomasz S. Zabkowski, Krzysztof Gajowniczek:
Extended AMUSE Algorithm and Novel Randomness Approach for BSS Model Aggregation with Methodology Remarks. ICAISC 2015: 527-537 - 2014
- [c20]Ryszard Szupiluk, Tomasz S. Zabkowski:
Signal Randomness Measure for BSS Ensemble Predictors. ICAISC (2) 2014: 570-578 - [c19]Krzysztof Gajowniczek, Tomasz S. Zabkowski:
Short Term Electricity Forecasting Using Individual Smart Meter Data. KES 2014: 589-597 - 2013
- [c18]Ryszard Szupiluk, Tomasz S. Zabkowski:
A State Space Approach and Hurst Exponent for Ensemble Predictors. EANN (1) 2013: 154-164 - [c17]Ryszard Szupiluk, Piotr Wojewnik, Tomasz S. Zabkowski:
Independent Component Analysis Filtration for Value at Risk Modelling. ICANN 2013: 553-562 - [c16]Ryszard Szupiluk, Tomasz S. Zabkowski:
Similarity Analysis Based on Bose-Einstein Divergences for Financial Time Series. ICANNGA 2013: 417-427 - 2012
- [c15]Ryszard Szupiluk, Piotr Wojewnik, Tomasz S. Zabkowski:
Multiplicative ICA Algorithm for Interaction Analysis in Financial Markets. ICAISC (2) 2012: 608-615 - [c14]Ryszard Szupiluk, Piotr Wojewnik, Tomasz S. Zabkowski:
Smooth Component Analysis and MSE Decomposition for Ensemble Methods. KES-AMSTA 2012: 595-603 - 2011
- [c13]Ryszard Szupiluk, Piotr Wojewnik, Tomasz S. Zabkowski:
The Noise Identification Method Based on Divergence Analysis in Ensemble Methods Context. ICANNGA (2) 2011: 206-214 - [c12]Ryszard Szupiluk, Piotr Wojewnik, Tomasz S. Zabkowski:
Multistage Covariance Approach to Measure the Randomness in Financial Time Series Analysis. KES-AMSTA 2011: 610-619 - 2010
- [c11]Ryszard Szupiluk, Piotr Wojewnik, Tomasz S. Zabkowski:
Noise Detection for Ensemble Methods. ICAISC (1) 2010: 471-478 - [c10]Ryszard Szupiluk, Piotr Wojewnik, Tomasz S. Zabkowski:
Aggregated Information Representation for Technical Analysis on Stock Market with Csiszár Divergence. KES-AMSTA (2) 2010: 272-281 - 2008
- [c9]Ryszard Szupiluk, Piotr Wojewnik, Tomasz S. Zabkowski:
Generalized Extreme Value for Smooth Component Analysis in Prediction Improvement. KES (1) 2008: 749-756 - 2007
- [c8]Ryszard Szupiluk, Piotr Wojewnik, Tomasz S. Zabkowski:
Smooth Component Analysis as Ensemble Method for Prediction Improvement. ICA 2007: 277-284 - 2006
- [c7]Ryszard Szupiluk, Piotr Wojewnik, Tomasz S. Zabkowski:
Combining Forecasts with Blind Signal Separation Methods in Electric Load Prediction Framework. Artificial Intelligence and Applications 2006: 439-444 - [c6]Ryszard Szupiluk, Piotr Wojewnik, Tomasz S. Zabkowski:
Blind Signal Separation Methods for Integration of Neural Networks Results. FUSION 2006: 1-6 - [c5]Ryszard Szupiluk, Piotr Wojewnik, Tomasz S. Zabkowski:
Prediction Improvement via Smooth Component Analysis and Neural Network Mixing. ICANN (2) 2006: 133-140 - 2005
- [c4]Krzysztof Siwek, Stanislaw Osowski, Ryszard Szupiluk, Piotr Wojewnik, Tomasz S. Zabkowski:
Blind source separation for improved load forecasting in the power system. ECCTD 2005: 61-64 - [c3]Ryszard Szupiluk, Piotr Wojewnik, Tomasz S. Zabkowski:
PCA and ICA Methods for Prediction Results Enhancement. Intelligent Information Systems 2005: 387-394 - 2004
- [c2]Ryszard Szupiluk, Piotr Wojewnik, Tomasz S. Zabkowski:
Model Improvement by the Statistical Decomposition. ICAISC 2004: 1199-1204 - [c1]Ryszard Szupiluk, Piotr Wojewnik, Tomasz S. Zabkowski:
Independent Component Analysis for Filtration in Data Mining. Intelligent Information Systems 2004: 117-125
Coauthor Index
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