Presented By
O’Reilly + Cloudera
Make Data Work
29 April–2 May 2019
London, UK
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Fair, privacy-preserving, and secure ML

Mikio Braun (Zalando)
14:0514:45 Wednesday, 1 May 2019
Data Science, Machine Learning & AI, Expo Hall
Location: Expo Hall (Capital Hall N24)
Secondary topics:  Security and Privacy
Average rating: *****
(5.00, 3 ratings)

What you'll learn

  • Explore techniques and concepts around fairness, privacy, and security


As machine learning becomes mainstream, the side effects of using machine learning and AI on our lives have become increasingly visible. However, awareness for preserving privacy in ML models is rapidly growing. Companies have learned, often through painful experience, that you have to take extra measures to make machine learning models fair and unbiased. For example, we now know it’s possible that private data within training examples can be retrieved from a learned model without extra measures.

Mikio Braun explores techniques and concepts around fairness, privacy, and security when it comes to machine learning models.

Photo of Mikio Braun

Mikio Braun


Mikio Braun is a principal engineer for search at Zalando, one of Europe’s biggest fashion platforms. He worked in research for a number of years before becoming interested in putting research results to good use in the industry. Mikio holds a PhD in machine learning.