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.
When
–
Where
Online
Event language(s)
English
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.
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