Deep Learning: Differential Privacy

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.

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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 contact@vdlm.at

Please note that this meetup has a limited capacity of 100 participants (we allow slightly more signups due to usual no-shows).

We are looking forward to seeing you!