الباحثون

Raoof Zare Moayedi

المنشورات 2

نسخة أولية وصول مفتوح

Transferable Adversarial Robustness for Speech Foundation Models via Hierarchical Stabilization

Frozen speech foundation models (SFMs) make downstream adaptation efficient: the backbone can stay fixed while a task learns layer fusion and a lightweight classifier. Full adversarial fine-tuning is a standard route to robustness, but generating adversarial examples and updating the backbone for every task sacrifices …

نسخة أولية وصول مفتوح

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} …

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