Idiap Research Institute organizes an online AIDA short course on Trustworthy ML offered through the International Artificial Intelligence Doctoral Academy (AIDA).
The purpose of this course is to overview the foundations and the current state-of-the-art in differentially private ML and adversarial examples for privacy protection.
This short course will cover the following topics:
- Introduction and motivation (privacy and personal data)
- Differential privacy
1. Definitions
1. Differentially private machine learning
- Adversarial examples
1. Adversarial goals, knowledge, and properties
1. Defenses against adversarial examples
1. Norm-bounded and content-based adversarial examples
- Adversarial examples for privacy protection
1. Privacy and utility for images/audio in social multimedia
- Hands-on examples (with software modules distributed to the participants)
LECTURER:
– Sina Sajadmanesh, email: sajadmanesh@idiap.ch
– Ali Shahin Shamsabadi, email: a.shahinshamsabadi@turing.ac.uk
– Daniel Gatica Perez, email: gatica@idiap.ch
HOST INSTITUTION/ORGANIZER: IDIAP
REGISTRATION: Free of charge.
WHEN: 23-24 November 2022 from 10:00 to 13:00 CET
WHERE: Online via Zoom
HOW TO REGISTER and ENROLL:
Both AIDA and non-AIDA students are encouraged to participate in this short course.
If you are an AIDA Student* already, please:
Step (a) register for the course by sending an email to sajadmanesh@idiap.ch, AND
Step (b) enroll in the same course in the AIDA system using the enrollment button on the AIDA course page, so that this course enters your AIDA Course Attendance Certificate.
If you are not an AIDA Student do only step (a).
*AIDA Students should have been registered in the AIDA system already (they are PhD students or PostDocs that belong only to the AIDA Members listed on this page:
https://www.i-aida.org/about/members/)
Sina Sajadmanesh
Email sajadmanesh@idiap.ch
More details: https://www.i-aida.org/course/an-introduction-to-trustworthy-machine-learning/