IEEE SPS Seasonal School on Networked Federated Learning: Theory, Methods and Applications
The IEEE Finland Jt. Chapter SP/CAS is organising this seasonal school during March 2022.
Many important application domains generate distributed collections of local datasets. Networked federated learning allows to train tailored models for each local dataset in a col- laborative fashion.
This seasonal school teaches some of the theoretical and al- gorithmic underpinnings of federated learning. We illustrate key concepts using the toy example of a personalized Covid-19 diagnosis smartphone app.
This seasonal school is organised as three modules:
- Basics of Machine Learning
- Networked Data
- Networked Models
Each module consists of lectures and coding assignments with Python notebooks.
This seasonal school is inspired by the recent Live-Project by Alexander Jung, Assistant Professor for machine learning at the Department of Computer Science, Aalto University.