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ORCIDTomasz Górecki
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2020 – today
- 2024
[j20]Tomasz Górecki
, Maciej Luczak, Pawel Piasecki:
An exhaustive comparison of distance measures in the classification of time series with 1NN method. J. Comput. Sci. 76: 102235 (2024)- [c9]Krzysztof Dyczkowski, Bartlomiej Grzelak, Tomasz Górecki, Tomasz Pilka, Aleksandra Sadurska, Barbara Pekala, Adam Lee Owen:
Sensor-Based Injury Prediction in Football Using a New Interval-Valued Fuzzy Inference Library. FUZZ 2024: 1-8 - 2023
- [j19]Robert Kwiecinski, Grzegorz Melniczak, Tomasz Górecki:
Comparison of Real-Time and Batch Job Recommendations. IEEE Access 11: 20553-20559 (2023) - [j18]Tomasz Pilka, Bartlomiej Grzelak, Aleksandra Sadurska, Tomasz Górecki, Krzysztof Dyczkowski:
Predicting Injuries in Football Based on Data Collected from GPS-Based Wearable Sensors. Sensors 23(3): 1227 (2023) - [c8]Slawomir Pioronski, Tomasz Górecki:
Spotting Cyber Breaches in IoT Devices. FedCSIS 2023: 1307-1310 - [c7]Aleksandra Sadurska, Tomasz Pilka, Bartlomiej Grzelak, Tomasz Górecki, Krzysztof Dyczkowski, Michal Zareba:
Fusion of a Fuzzy Rule-Based Method and Other Decision-Making Models in Injury Prediction Problem in Football. FUZZ 2023: 1-6 - [c6]Slawomir Pioronski, Tomasz Górecki:
Predicting Player Performance in Tactical Games with the Lightgbm Algorithm. ICME Workshops 2023: 22-27 - [i2]Robert Kwiecinski, Agata Filipowska, Tomasz Górecki, Viacheslav Dubrov:
Job recommendations: benchmarking of collaborative filtering methods for classifieds. CoRR abs/2301.07946 (2023) - 2022
- [j17]Marek Niewiarowicz, Andrzej Wicher, Aleksander Sek, Tomasz Górecki:
Speech intelligibility deterioration for normal hearing and hearing impaired patients with different types of tinnitus. Speech Commun. 139: 35-44 (2022) - [c5]Slawomir Pioronski, Tomasz Górecki:
Using GAN to Generate Malicious Samples Suitable for Binary Classifier Training. IEEE Big Data 2022: 6522-6527 - [c4]Robert Kwiecinski, Tomasz Górecki, Agata Filipowska:
Learning edge importance in bipartite graph-based recommendations. FedCSIS 2022: 227-233 - [c3]Slawomir Pioronski, Tomasz Górecki:
Using gradient boosting trees to predict the costs of forwarding contracts. FedCSIS 2022: 421-424 - 2021
- [j16]Lukasz Borchmann, Dawid Jurkiewicz, Filip Gralinski, Tomasz Górecki:
Dynamic Boundary Time Warping for sub-sequence matching with few examples. Expert Syst. Appl. 169: 114344 (2021) - 2020
- [j15]Tomasz Górecki, Miroslaw Krzysko, Waldemar Wolynski:
Independence test and canonical correlation analysis based on the alignment between kernel matrices for multivariate functional data. Artif. Intell. Rev. 53(1): 475-499 (2020) - [j14]Tomasz Górecki, Pawel Piasecki:
Generalization of the Procrustes coefficient to functional data. Commun. Stat. Simul. Comput. 49(3): 808-816 (2020) - [i1]Lukasz Borchmann, Dawid Jurkiewicz, Filip Gralinski, Tomasz Górecki:
Dynamic Boundary Time Warping for Sub-sequence Matching with Few Examples. CoRR abs/2010.14464 (2020)
2010 – 2019
- 2019
- [j13]Tomasz Górecki, Lukasz Smaga:
fdANOVA: an R software package for analysis of variance for univariate and multivariate functional data. Comput. Stat. 34(2): 571-597 (2019) - [j12]Tomasz Górecki, Maciej Luczak:
The influence of the Sakoe-Chiba band size on time series classification. J. Intell. Fuzzy Syst. 36(1): 527-539 (2019) - [c2]Filip Gralinski, Anna Wróblewska, Tomasz Stanislawek, Kamil Grabowski, Tomasz Górecki:
GEval: Tool for Debugging NLP Datasets and Models. BlackboxNLP@ACL 2019: 254-262 - 2018
- [j11]Tomasz Górecki:
Classification of time series using combination of DTW and LCSS dissimilarity measures. Commun. Stat. Simul. Comput. 47(1): 263-276 (2018) - 2016
- [j10]Tomasz Górecki, Maciej Luczak:
Evolutionarily Tuned Generalized Pseudo-Inverse in Linear Discriminant Analysis. Comput. Informatics 35(3): 615-634 (2016) - 2015
- [j9]Tomasz Górecki, Miroslaw Krzysko:
Regression Methods for Combining Multiple Classifiers. Commun. Stat. Simul. Comput. 44(3): 739-755 (2015) - [j8]Tomasz Górecki, Lukasz Smaga:
A comparison of tests for the one-way ANOVA problem for functional data. Comput. Stat. 30(4): 987-1010 (2015) - [j7]Tomasz Górecki, Maciej Luczak:
Multivariate time series classification with parametric derivative dynamic time warping. Expert Syst. Appl. 42(5): 2305-2312 (2015) - 2014
- [j6]Tomasz Górecki, Maciej Luczak:
First and Second Derivatives in Time Series Classification Using DTW. Commun. Stat. Simul. Comput. 43(9): 2081-2092 (2014) - [j5]Tomasz Górecki, Maciej Luczak:
Non-isometric transforms in time series classification using DTW. Knowl. Based Syst. 61: 98-108 (2014) - [j4]Tomasz Górecki:
Using derivatives in a longest common subsequence dissimilarity measure for time series classification. Pattern Recognit. Lett. 45: 99-105 (2014) - [c1]Tomasz Górecki, Miroslaw Krzysko, Waldemar Wolynski:
Multivariate Functional Regression Analysis with Application to Classification Problems. ECDA 2014: 173-183 - 2013
- [j3]Tomasz Górecki, Maciej Luczak:
Linear discriminant analysis with a generalization of the Moore-Penrose pseudoinverse. Int. J. Appl. Math. Comput. Sci. 23(2): 463-471 (2013) - [j2]Tomasz Górecki, Maciej Luczak:
Using derivatives in time series classification. Data Min. Knowl. Discov. 26(2): 310-331 (2013) - 2010
- [j1]Tomasz Górecki, Maciej Luczak:
Some Methods of Replacing the Nearest Neighbor Method. Commun. Stat. Simul. Comput. 39(2): 262-276 (2010)
Coauthor Index
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