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Shuang Song

6 أوراق في مجموعة PaperMetrix

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أوراق هذا المؤلف

  1. Encode, Shuffle, Analyze Privacy Revisited: Formalizations and Empirical Evaluation

    2020 · arXiv (Cornell University)

    Recently, a number of approaches and techniques have been introduced for reporting software statistics with strong privacy guarantees. These range from abstract algorithms to comprehensive systems with varying assumptions and built upon local differential privacy …

  2. Evading Curse of Dimensionality in Unconstrained Private GLMs via Private Gradient Descent

    2020 · arXiv (Cornell University)

    We revisit the well-studied problem of differentially private empirical risk minimization (ERM). We show that for unconstrained convex generalized linear models (GLMs), one can obtain an excess empirical risk of $\tilde O\left(\sqrt{\texttt{rank}}/εn\right)$, where ${\texttt{rank}}$ is …

  3. EANA: Reducing Privacy Risk on Large-scale Recommendation Models

    2022

    Embedding-based deep neural networks (DNNs) are widely used in large-scale recommendation systems. Differentially-private stochastic gradient descent (DP-SGD) provides a way to enable personalized experiences while preserving user privacy by injecting noise into every model parameter …

  4. Automatic segmentation of thyroid nodule from ultrasound images using spatial-channel attentive U-Net

    2022

    The ultrasound image is a commonly used imaging modality to treat thyroid nodules due to its rapid imaging speed and the ability for multiple anatomical and soft-tissue visualization. However, considering the variability of the position, …

  5. Move Smart Contract Vulnerability Detection based on Resource-flow Analysis

    2023

    The Move smart contract (MSC) is designed to enhance the type security of digital assets by utilizing a resource-based structure. However, vulnerabilities may be introduced during the development process. In response to the security threats …

  6. The Attacker Moves Second: Stronger Adaptive Attacks Bypass Defenses Against Llm Jailbreaks and Prompt Injections

    2025 · arXiv (Cornell University)

    How should we evaluate the robustness of language model defenses? Current defenses against jailbreaks and prompt injections (which aim to prevent an attacker from eliciting harmful knowledge or remotely triggering malicious actions, respectively) are typically …