← Search

Xiaotian Chang

2 accepted papers

2026

Exponential-Wrapped Mechanisms: Differential Privacy on Hadamard Manifolds Made Practical

ICLR 2026poster

We propose a general and computationally efficient framework for achieving differential privacy (DP) on Hadamard manifolds, which are complete and simply connected Riemannian manifolds with non-positive curvature. Leveraging the Cartan-Hadamard theorem, we introduce Exponential-Wrapped Laplace and G…

Cited by 0SourceScholar
2023

Gaussian Differential Privacy on Riemannian Manifolds

NeurIPS 2023poster

We develop an advanced approach for extending Gaussian Differential Privacy (GDP) to general Riemannian manifolds. The concept of GDP stands out as a prominent privacy definition that strongly warrants extension to manifold settings, due to its central limit properties. By harnessing the power of th…