Hello dear Deep Learners,
Happy New Year! We kindly invite you to our first Deep Learning meetup in 2024 on January 17, hosted by Dynatrace in the Icon Tower at Wien Hauptbahnhof (central station)! Our topic will be Differential Privacy for Machine Learning.
Agenda
18:30
Introduction by the VDLM organizers
Welcome by the host
18:40
Differential Privacy for Machine Learning
Anastasia Pustozerova - Researcher at SBA Research and TU Wien.
Announcements & Job Openings
(optional) Hot Topics & Latest News
19:45
Networking & Discussions
21:30 Wrap up & End
Talk Abstract: Differential Privacy for Machine Learning
Machine Learning requires a lot of data to train effective models. Data owners might not be willing to share the data because of its private nature. Differential Privacy can help to quantify and enhance the privacy of sensitive data, when performing data analysis or machine learning. Companies including Apple, Google, Microsoft and even governments employ Differential Privacy to gain insights into the data while preserving the privacy of individual users. But what is Differential Privacy? How can it make machine learning more private? Most importantly, does it actually always guarantee the privacy of individuals? This talk will provide you with the answers and an understanding of why, when and how to use Differential Privacy in a meaningful way.
Hot Topics & Latest News:
Do you have some interesting breaking news about Deep Learning? Did you read an interesting paper that you want to share? Did you create an exciting application or achieve some break-through? It would be great to share this in our meetup's Hot Topics section! Please get in touch through [email protected]