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English(EN) A Typed Tensor Language for Shared-State Federated Computation

新的类型化张量语言支持共享状态联邦计算

一种新的类型化张量语言已被开发出来,用于促进共享状态联邦计算,该计算将客户端本地张量操作与聚合共享状态相结合。该语言使用两种张量排序来区分客户端分区数据和全局可用值,并跟踪分区轴。它使类型化的单轮程序能够通过共享张量进行分解,其中编码器组件由聚合或收缩表示,而解码器仅共享。该系统扩展到具有持久共享状态的多轮程序,并支持用于联邦分析和FedSGD的服务器端一阶和曲率块更新。 AI

影响 这种新语言可以简化联邦学习模型的开发和执行,有可能提高分布式人工智能训练的效率和可扩展性。

排序理由 该集群包含一篇学术论文,详细介绍了一种用于特定类型计算的新技术语言。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新的类型化张量语言支持共享状态联邦计算

本文如何被排名

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该集群包含一篇学术论文,详细介绍了一种用于特定类型计算的新技术语言。[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) · Theofilos Mailis, Theodore Papamarkou, Andreas Ktenidis, Kalliopi-Christina Despotidou, Konstantinos Filippopolitis, Yannis Foufoulas, Thanasis-Michail Karampatsis, Evdokia Mailli, Yannis Ioannidis ·

    面向共享状态联邦计算的类型化张量语言

    arXiv:2605.21103v2 Announce Type: replace Abstract: Shared-state federated computations combine client-local tensor computation, mergeable aggregation into shared state, and shared-only post-processing. We introduce a typed tensor language for this class of computations. Its two …