Since its inception in 1982, Oja's algorithm has become an established method for
streaming principle component analysis (PCA). We study the problem of streaming PCA …

We investigate the concept of utility-preserving federated learning (UPFL) in the context of
deep neural networks. We theoretically prove and experimentally validate that UPFL …

Federated learning (FL) is emerging as a privacy-aware alternative to classical cloud-based
machine learning. In FL, the sensitive data remains in data silos and only aggregated …

Abstract Artificial Intelligence (AI) and Machine Learning (ML) methods have been applied
significantly in modern healthcare systems in the last few years. AI and its subfields, such as …

The ongoing transition from a linear (produce-use-dispose) to a circular economy poses
significant challenges to current state-of-the-art information and communication …

Combining training data from multiple sources increases sample size and reduces
confounding, leading to more accurate and less biased machine learning models. In …

Modern manufacturing value chains require intelligent orchestration of processes across
company borders in order to maximize profits while fostering social and environmental …

Federated learning (FL) is a privacy-aware data mining strategy keeping the private data on
the owners' machine and thereby confidential. The clients compute local models and send …

Motivation Federated learning enables privacy-preserving machine learning in the medical
domain because the sensitive patient data remain with the owner and only parameters are …

The ongoing transition from a linear (produce-use-dispose) to a circular economy poses
significant challenges to current state-of-the-art information and communication …