Tomasz Wiktorski
Orcid: 0000-0002-5940-8102
According to our database1,
Tomasz Wiktorski
authored at least 31 papers
between 2015 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
On csauthors.net:
Bibliography
2024
The intentions of the designers of digital educational tools in early childhood education.
Int. J. Child Comput. Interact., 2024
Machine Learning Methods For Classification of Individuals With Coronary Artery Calcification.
Proceedings of the 37th IEEE International Symposium on Computer-Based Medical Systems, 2024
2023
Improving predictive models for rate of penetration in real drilling operations through transfer learning.
J. Comput. Sci., September, 2023
Better Modeling Out-of-Distribution Regression on Distributed Acoustic Sensor Data Using Anchored Hidden State Mixup.
IEEE Trans. Ind. Informatics, 2023
2022
Better Modelling Out-of-Distribution Regression on Distributed Acoustic Sensor Data Using Anchored Hidden State Mixup.
CoRR, 2022
Proceedings of the Computational Science - ICCS 2022, 2022
2021
A Survey on Distributed Fibre Optic Sensor Data Modelling Techniques and Machine Learning Algorithms for Multiphase Fluid Flow Estimation.
Sensors, 2021
EDISON Data Science Framework (EDSF): Addressing Demand for Data Science and Analytics Competences for the Data Driven Digital Economy.
Proceedings of the IEEE Global Engineering Education Conference, 2021
2020
Sensors, 2020
2019
Advanced Information and Knowledge Processing, Springer, ISBN: 978-3-030-04602-6, 2019
Concurr. Comput. Pract. Exp., 2019
Proceedings of the 2019 International Conference on Data Mining Workshops, 2019
Data Science Model Curriculum Implementation for Various Types of Big Data Infrastructure Courses.
Proceedings of the 15th International Conference on eScience, 2019
EDISON Data Science Framework (EDSF) Extension to Address Transversal Skills Required by Emerging Industry 4.0 Transformation.
Proceedings of the 15th International Conference on eScience, 2019
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019
2018
J. Autom. Mob. Robotics Intell. Syst., 2018
Proceedings of the Position Papers of the 2018 Federated Conference on Computer Science and Information Systems, 2018
ECG Signal Analysis for Troponin Level Assessment and Coronary Artery Disease Detection: the NEEDED Study 2014.
Proceedings of the 2018 Federated Conference on Computer Science and Information Systems, 2018
2017
Concurr. Comput. Pract. Exp., 2017
Proceedings of the IEEE International Conference on Cloud Computing Technology and Science, 2017
Customisable Data Science Educational Environment: From Competences Management and Curriculum Design to Virtual Labs On-Demand.
Proceedings of the IEEE International Conference on Cloud Computing Technology and Science, 2017
2016
Enrichment of machine learning based activity classification in smart homes using ensemble learning.
Proceedings of the 9th International Conference on Utility and Cloud Computing, 2016
Adaptive Anomaly Detection in Cloud Using Robust and Scalable Principal Component Analysis.
Proceedings of the 15th International Symposium on Parallel and Distributed Computing, 2016
Quantitative and Qualitative Analysis of Current Data Science Programs from Perspective of Data Science Competence Groups and Framework.
Proceedings of the 2016 IEEE International Conference on Cloud Computing Technology and Science, 2016
EDISON Data Science Framework: A Foundation for Building Data Science Profession for Research and Industry.
Proceedings of the 2016 IEEE International Conference on Cloud Computing Technology and Science, 2016
Proceedings of the 2016 IEEE International Congress on Big Data, San Francisco, CA, USA, June 27, 2016
2015
AFFM: Auto Feature Engineering in Field-Aware Factorization Machines for Predictive Analytics.
Proceedings of the IEEE International Conference on Data Mining Workshop, 2015
Proceedings of the 7th IEEE International Conference on Cloud Computing Technology and Science, 2015
Data Science Professional Uncovered: How the EDISON Project will Contribute to a Widely Accepted Profile for Data Scientists.
Proceedings of the 7th IEEE International Conference on Cloud Computing Technology and Science, 2015
Analyzing and Predicting Failure in Hadoop Clusters Using Distributed Hidden Markov Model.
Proceedings of the Cloud Computing and Big Data, 2015