The goal of INTERACTIVE is to design and develop workflows and algorithmic methods that enable machine learning in distributed edge computing environments despite missing or insufficient ground-truth data.
Federated Learning enables decentralized devices to collaboratively learn a shared prediction model while keeping all the training data on decentralized devices withoutstoring the data in the cloud.
Active learning denotes a machine learning method that enables interactive machine learning workflows by integrating human feedback into the learning process.
Industrial Data Science
Our Data Analytics approaches span the entire data science lifecycle, from data preparation to data analysis and modeling to predictive model deployment