Jȩdrzej Kozal

Jȩdrzej Kozal
Wroclaw University of Science and Technology | WUT · Faculty of Information and Communication Technology

Master of Science

About

5
Publications
291
Reads
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1
Citation
Additional affiliations
December 2019 - October 2021
Samsung
Position
  • Junior Machine Learning Engineer
Education
February 2018 - July 2019
Wroclaw University of Science and Technology
Field of study
  • Computer Science
October 2014 - January 2018
Wrocław University of Science and Technology
Field of study
  • Robotics and Control Engineering

Publications

Publications (5)
Preprint
Full-text available
The abundance of information in digital media, which in today's world is the main source of knowledge about current events for the masses, makes it possible to spread disinformation on a larger scale than ever before. Consequently, there is a need to develop novel fake news detection approaches capable of adapting to changing factual contexts and g...
Article
Full-text available
Modern analytical systems must process streaming data and correctly respond to data distribution changes. The phenomenon of changes in data distributions is called concept drift , and it may harm the quality of the used models. Additionally, the possibility of concept drift appearance causes that the used algorithms must be ready for the continuous...
Preprint
Full-text available
Increasing neural network depth is a well-known method for improving neural network performance. Modern deep architectures contain multiple mechanisms that allow hundreds or even thousands of layers to train. This work is trying to answer if extending neural network depth may be beneficial in a life-long learning setting. In particular, we propose...
Preprint
Full-text available
Modern analytical systems must be ready to process streaming data and correctly respond to data distribution changes. The phenomenon of changes in data distributions is called concept drift, and it may harm the quality of the used models. Additionally, the possibility of concept drift appearance causes that the used algorithms must be ready for the...
Chapter
Full-text available
In this work we explored capabilities of improving deep learning models performance by reducing the dataset imbalance. For our experiments a highly imbalanced ECG dataset MIT-BIH was used. Multiple approaches were considered. First we introduced mutliclass UMCE, the ensemble designed to deal with imbalanced datasets. Secondly, we studied the impact...

Projects

Project (1)
Project
Objectives: A. New development in the drift concept area. B. Advanced streaming data research using recurrent systems. C. Lifelong learning on streaming data. This project involves researchers from Faculty of Electrical Engineering and Computer Science (FEI), VŠBTechnical University of Ostrava and the Department of Systems and Computer Networks, Wroclaw University of Science and Technology.