1 citations · 1 across the 6 of their papers we have counts for
4 papers · 1 filter
Computation-Utility-Privacy Tradeoffs in Bayesian Estimation
Sitan Chen, Jingqiu Ding, Mahbod Majid +1
Bayesian methods lie at the heart of modern data science and provide a powerful scaffolding for estimation in data-constrained settings and principled quantification and propagatio…
Improved Robust Estimation for Erdős-Rényi Graphs: The Sparse Regime and Optimal Breakdown Point
Hongjie Chen, Jingqiu Ding, Yiding Hua +1
We study the problem of robustly estimating the edge density of Erdős-Rényi random graphs when an adversary can arbitrarily add or remove edges incident to an …
Private Edge Density Estimation for Random Graphs: Optimal, Efficient and Robust
Hongjie Chen, Jingqiu Ding, Yiding Hua +1
We give the first polynomial-time, differentially node-private, and robust algorithm for estimating the edge density of Erdős-Rényi random graphs and their generalization, inhomoge…
Private graphon estimation via sum-of-squares
Hongjie Chen, Jingqiu Ding, Tommaso d'Orsi +3
We develop the first pure node-differentially-private algorithms for learning stochastic block models and for graphon estimation with polynomial running time for any constant numbe…