23 citations · 40 across the 5 of their papers we have counts for
5 papers
Comparing the Utility and Disclosure Risk of Synthetic Data with Samples of Microdata
Claire Little, Mark Elliot, Richard Allmendinger
Most statistical agencies release randomly selected samples of Census microdata, usually with sample fractions under 10% and with other forms of statistical disclosure control (SDC…
Generative Adversarial Networks for Synthetic Data Generation: A Comparative Study
Claire Little, Mark Elliot, Richard Allmendinger +1
Generative Adversarial Networks (GANs) are gaining increasing attention as a means for synthesising data. So far much of this work has been applied to use cases outside of the data…
Provenance, Anonymisation and Data Environments: a Unifying Construction
Muhammad Aslam Jarwar, Adriane Chapman, Mark Elliot +1
The Anonymisation Decision-making Framework (ADF) operationalizes the risk management of data exchange between organizations, referred to as "data environments". The second edition…
The future of statistical disclosure control
Mark Elliot, Josep Domingo-Ferrer
Statistical disclosure control (SDC) was not created in a single seminal paper nor following the invention of a new mathematical technique, rather it developed slowly in response t…
Breaking the Activation Function Bottleneck through Adaptive Parameterization
Sebastian Flennerhag, Hujun Yin, John Keane +1
Standard neural network architectures are non-linear only by virtue of a simple element-wise activation function, making them both brittle and excessively large. In this paper, we…