Author

Vahid R. Asadi

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Preprint Sep 2026

Improved Quantum Random Self-Reduction for Linear Problems

We study quantum random self-reductions for linear problems over finite fields. Let $M\in\mathbb{F}^{n\times n}$ be an arbitrary matrix, and let $\mathcal{O}$ be an oracle that agrees with the linear map $x\mapsto Mx$ on an $\varepsilon$-fraction of inputs $x\sim\mathbb{F}^n$. Given coherent access to $\mathcal{O}$ and...

Vahid R. Asadi, Shuichi Hirahara, Nobutaka Shimizu · 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