Federated Learning (FL) represents a paradigm shift in the field of machine learning,
offering an approach for a decentralized training of models across a multitude of devices …

In this comprehensive study, we employed a versatile approach to tackle the prediction
challenges associated with atrial fibrillation (AF) and cardiovascular events (CE). Exploiting …

We propose a method to generate statistically representative synthetic data. The main goal
is to be able to maintain in the synthetic dataset the correlations of the features present in the …

Production is becoming increasingly flexible, which also requires the flexibility of the support
system for the production. And the key here is the speed of decisions, in which the support of …

Good warranty data is scarce, and even data that has been collected reliably is subject to
censoring. This can limit the amount of data available for conducting warranty cost analysis …

Tämän kandidaatintyön tavoitteena on selvittää kuinka teollisuusyritykset pystyvät
hyödyntämään synteettistä dataa liiketoiminnassaan. Työssä tarkastellaan datapohjaiseen …

Solving the small sample problem can not only save data acquisition costs, but also
enhance the model's generalization ability to unknown data, thereby ensuring the accuracy …