activity
20232026
collaborators

5 papers

math.ST2026

Statistical Properties of Nonparametric MLE under Laplace Noise

Yifei Xiong, Nianqiao Phyllis Ju, Vinayak Rao

Local differential privacy (LDP) protects individuals in a dataset by perturbing each measurement before release. For real-valued data, a widely used mechanism is additive Laplace…

stat.ME2025

SOMA: A Novel Sampler for Bayesian Inference from Privatized Data

Yifei Xiong, Nianqiao Phyllis Ju

Making valid statistical inferences from privatized data is a key challenge in modern analysis. In Bayesian settings, data augmentation MCMC (DAMCMC) methods impute unobserved conf…

stat.CO2024

Leveraging Nested MLMC for Sequential Neural Posterior Estimation with Intractable Likelihoods

Xiliang Yang, Yifei Xiong, Zhijian He

There is a growing interest in studying sequential neural posterior estimation (SNPE) techniques due to their advantages for simulation-based models with intractable likelihoods. T…

stat.ML2023

An efficient likelihood-free Bayesian inference method based on sequential neural posterior estimation

Yifei Xiong, Xiliang Yang, Sanguo Zhang +1

Sequential neural posterior estimation (SNPE) techniques have been recently proposed for dealing with simulation-based models with intractable likelihoods. Unlike approximate Bayes…

stat.ML2023

Simulation-based Bayesian Inference from Privacy Protected Data

Yifei Xiong, Nianqiao Phyllis Ju, Sanguo Zhang

Many modern statistical analysis and machine learning applications require training models on sensitive user data. Under a formal definition of privacy protection, differentially p…