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Apple ML Research 推出用于大型数据的快速交互式证明

作者 PulseAugur 编辑部 · [1 个来源] ·

Apple Machine Learning Research 发表了一篇论文，详细介绍了“Doubly Sub-linear Interactive Proofs of Proximity”（dsIPPs）。这些证明允许通过仅读取大型输入的一小部分来实现超快速生成，并且近似验证速度更快。该研究为可由恒定宽度单次读取的不可知分支程序决定的属性构建了这样的证明系统，并探讨了用于证明关于输入汉明权重和图双向性的近似断言的应用。 AI

影响 引入了新颖的证明系统，可以提高验证大型数据集中属性的效率，可能影响 AI 模型的训练和验证。

排序理由 由一家主要科技公司研究部门发表的学术论文。 [lever_c_demoted from research: ic=1 ai=0.7]

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Apple ML Research 推出用于大型数据的快速交互式证明

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由一家主要科技公司研究部门发表的学术论文。 [lever_c_demoted from research: ic=1 ai=0.7]
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报道来源 [1]

  1. Apple Machine Learning Research TIER_1 English(EN) ·

    Doubly Sub-linear Interactive Proofs of Proximity

    We study doubly sub-linear interactive proofs of proximity (dsIPPs): proofs that are ultra-fast to generate, and can be used to prove approximate assertions about a huge input. Proof generation is ultra-fast in the sense that it only requires reading a small (sub-linear) portion …

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