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This project is about building competitive methods for NeurIPS 2020 Hide-and-Seek Privacy Challenge: https://www.vanderschaar-lab.com/privacy-challenge/ Competing in this challenge would also be a challenge since the deadline is quite soon (November 15th, 2020), however submitting a reasonable method to this challenge guarantees at least a grade 4 for the thesis. More realistically, the aim is to take up the same challenge and tackle it throughout your thesis. It provides a great platform with freely accessible dataset and open-source contributions. An evaluation set will be available only to the contributors after the deadline, so it is advantageous to enter the competition officially. The tasks are: - Hide: Generate synthetical data based on the original dataset so that it is similar to the real data but privacy-preserving (robust to re-identification) - Seek: Classify (re-identify) people accurately from synthetical datasets The students who are interested in this thesis must have a strong theoretical background in statistics, probability and machine learning and high grades from corresponding courses.
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