新方法用于信道模拟，有助于压缩和隐私

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-14 04:00

研究人员开发了一种新的离散到连续信道模拟方法，可应用于压缩和隐私任务。该方法使用固定数量的随机样本，使其运行时间独立于信道和输入，这与之前可能需要无限数量样本的方法不同。该方案在样本数量和压缩率之间提供了灵活的权衡，并已通过使用高斯机制的可变速率压缩和差分隐私分布式均值估计进行了演示。 AI

影响这项研究引入了一种新颖的模拟技术，可以提高机器学习中压缩和隐私应用的效率。

排序理由该集群包含一篇发表在 arXiv 上的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.LG TIER_1 English(EN) · Joseph Rowan, Buu Phan, Ashish J. Khisti · 2026-09-14 04:00

可扩展的离散到连续信道仿真，用于压缩和隐私

arXiv:2609.12067v1 Announce Type: new Abstract: Channel simulation has recently emerged as a useful component in machine learning systems where samples from a prescribed probability distribution are to be compressed. Yet, general channel simulation algorithms often suffer from hi…