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English(EN) Robustifying Asynchronous SGD via Soft Throttling

新的 Throttle 算法增强了异步 SGD 的鲁棒性和性能

研究人员开发了一种名为 Throttle 的新算法,它是异步 SGD 的拜占庭鲁棒泛化。该方法通过指数级地降低来自更快客户端的更新的权重来解决标准异步 SGD 中的漏洞。Throttle 提供了理论收敛保证,并对其实施攻击的鲁棒性进行了实证验证。有趣的是,即使不存在拜占庭攻击,这种降权机制也比标准异步 SGD 表现出更好的性能。 AI

影响 引入了一种新颖的算法方法,可以提高分布式机器学习训练的鲁棒性和效率。

排序理由 该集群描述了一篇研究论文中提出的一种新算法,详细介绍了其理论分析和实证验证。[lever_c_demoted from research: ic=1 ai=1.0]

在 Hugging Face Daily Papers 阅读 →

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新的 Throttle 算法增强了异步 SGD 的鲁棒性和性能

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该集群描述了一篇研究论文中提出的一种新算法,详细介绍了其理论分析和实证验证。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    通过软节流增强异步 SGD 的鲁棒性

    Asynchronous SGD is a popular algorithm for distributed learning where each client's gradient update is applied on arrival. This leads to a speed-up, but also an increased vulnerability to attacks, as fast clients can dominate the total update. We introduce Throttle, a Byzantine-…