Statistical Inference for Privatized Data with Unknown Sample Size
The discussion focuses on a paper titled "Statistical Inference for Privatized Data with Unknown Sample Size." The hosts explore how statistical analysis remains valid and converges when data counts are unknown due to privacy constraints. They review the theoretical proofs, the 'plug-in' strategy, and new computational tools like MCMC.