Author

Amir R. Asadi

h-index 3 View on Semantic Scholar

We have 2 of 7 papers

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

#machine learning Preprint Sep 2026

Geometry-Adaptive Mechanisms for Private Synthetic Data

Generating differentially private synthetic data with meaningful Wasserstein utility guarantees is challenging in high dimensions. For datasets of size $n$ on $[0,1]^d$ with $d\ge2$, existing pure $\varepsilon$-differentially private mechanisms achieve expected $1$-Wasserstein error of order $(\varepsilon n)^{-1/d}...

Raoof Zare Moayedi, Amir R. Asadi, M. Yassaee et al. · 0 citations

Open access Jul 2026

VeriDP: Verifiable Differentially Private Training

VeriDP is presented, a framework for verifiable differentially private training that cryptographically enforces and proves the correct execution of differentially private stochastic gradient descent (DP-SGD) in zero knowledge, uniting differential privacy and verifiable computation for secure and auditable ML.

B. Abdolmaleki, Amir R. Asadi, Vahid R. Asadi et al. · Proceedings on Privacy Enhan... · 0 citations