392274 ISY Project: Privacy-Preserving Federated Learning (Pj) (SoSe 2022)
Contents, comment
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Short Description:
Privacy-preserving federated learning is an emerging machine learning paradigm that aims to learning
knowledge from data distributed on different places without requiring to transmitting the data to a
central server. This way, the privacy of the data can be preserved. This project aims to develop a
federated, communication efficient, secure federated learning framework that can training deep
learning models with distributed data.
Required skills (e.g. mandatory courses, if required)• Basic knowledge of machine learning
• Hands-on Python programming skills
In case this would not find enough interest for a team project, this project proposal would be also
offered (in reduced/modified form)• an individual project
• a project for only 2 students
Teaching staff
Dates ( Calendar view )
| Frequency | Weekday | Time | Format / Place | Period |
|---|
Subject assignments
| Module | Course | Requirements | |
|---|---|---|---|
| 39-M-Inf-GP Grundlagenprojekt Intelligente Systeme | weiteres Projekt | Ungraded examination
|
Student information |
The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.
- Address:
- SS2022_392274@ekvv.uni-bielefeld.de
- This address can be used by teaching staff, their secretary's offices as well as the individuals in charge of course data maintenance to send emails to the course participants. IMPORTANT: All sent emails must be activated. Wait for the activation email and follow the instructions given there.
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- Notes:
- Additional notes on the electronic mailing lists
- Last update basic details/teaching staff:
- Wednesday, February 9, 2022
- Last update times:
- Wednesday, February 9, 2022
- Last update rooms:
- Wednesday, February 9, 2022
- Type(s) / SWS (hours per week per semester)
- project (Pj) / 2
- Language
- This lecture is taught in english
- Department
- Faculty of Technology
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- https://ekvv.uni-bielefeld.de/kvv_publ/publ/vd?id=334967858
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- ID
- 334967858