no code implementations • 2 Mar 2022 • Oscar Giles, Kasra Hosseini, Grigorios Mingas, Oliver Strickson, Louise Bowler, Camila Rangel Smith, Harrison Wilde, Jen Ning Lim, Bilal Mateen, Kasun Amarasinghe, Rayid Ghani, Alison Heppenstall, Nik Lomax, Nick Malleson, Martin O'Reilly, Sebastian Vollmerteke
Synthetic datasets are often presented as a silver-bullet solution to the problem of privacy-preserving data publishing.
no code implementations • 24 Aug 2021 • Sahra Ghalebikesabi, Harrison Wilde, Jack Jewson, Arnaud Doucet, Sebastian Vollmer, Chris Holmes
Increasing interest in privacy-preserving machine learning has led to new and evolved approaches for generating private synthetic data from undisclosed real data.
no code implementations • 16 Nov 2020 • Harrison Wilde, Jack Jewson, Sebastian Vollmer, Chris Holmes
There is significant growth and interest in the use of synthetic data as an enabler for machine learning in environments where the release of real data is restricted due to privacy or availability constraints.
1 code implementation • 30 Jul 2020 • Harrison Wilde, Lucia Lushi Chen, Austin Nguyen, Zoe Kimpel, Joshua Sidgwick, Adolfo De Unanue, Davide Veronese, Bilal Mateen, Rayid Ghani, Sebastian Vollmer
Rough sleeping is a chronic problem faced by some of the most disadvantaged people in modern society.