3 papers
math.ST2026
Bayesian Adversarial Privacy
Cameron Bell, Timothy Johnston, Antoine Luciano +1
Theoretical and applied research into privacy encompasses an incredibly broad swathe of differing approaches, emphases and aims. This work introduces a novel quantitative notion of…
stat.ME2025
Permutations accelerate Approximate Bayesian Computation
Antoine Luciano, Charly Andral, Christian P. Robert +1
Approximate Bayesian Computation (ABC) methods have become essential tools for performing inference when likelihood functions are intractable or computationally prohibitive. Howeve…
stat.ME2023
Insufficient Gibbs Sampling
Antoine Luciano, Christian P. Robert, Robin J. Ryder
In some applied scenarios, the availability of complete data is restricted, often due to privacy concerns; only aggregated, robust and inefficient statistics derived from the data…