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English(EN) Privacy-Preserving Deep Joint Source-Channel Coding with In-Loop Concept Erasure

新方法LEAPSC增强了深度联合信源信道编码的隐私性

研究人员开发了LEAPSC,一种用于隐私保护的深度联合信源信道编码的新方法。该技术将内循环最小二乘概念擦除集成到变分信息瓶颈编码器中,以防止在数据传输过程中泄露性别或种族等敏感属性。LEAPSC在CelebA和FairFace等数据集上表现出色,在保持攻击者准确率接近偶然水平的同时实现了高任务准确率,优于现有的对抗性基线。 AI

影响 为增强语义通信系统中的数据隐私性引入了一种新颖的技术。

排序理由 详细介绍一种新的隐私保护深度学习方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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新方法LEAPSC增强了深度联合信源信道编码的隐私性

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详细介绍一种新的隐私保护深度学习方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Rami Eid, Maria Slim, Mariette Awad, Hadi Sarieddeen ·

    具有内循环概念擦除的隐私保护深度联合信源信道编码

    arXiv:2609.13393v1 Announce Type: cross Abstract: Deep joint source-channel coding (DeepJSCC) transmits learned semantic features efficiently but can leak sensitive attributes such as gender, race, or speaker identity. We propose LEAPSC (LEACE-in-the-loop privacy for semantic com…