English(EN) Online Realizable Regression and Applications for ReLU Networks

新的潜在方法分析ReLU网络的可在线实现回归

作者 PulseAugur 编辑部 · [1 个来源] · 2026-06-16 04:00

研究人员开发了一种新的潜在方法来分析可在线实现回归，这是一个机器学习中的复杂问题。该方法基于Dudley型熵积分，为在线维度提供了上限，这对于理解此类回归任务的行为至关重要。这些发现为分析这些问题提供了一种更具体的方法，特别是对于ReLU网络，并对有限和无限累积损失界限都有影响。 AI

排序理由该集群包含一篇学术论文，详细介绍了一种分析机器学习回归问题的新理论方法。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.LG TIER_1 English(EN) · Ilan Doron-Arad, Idan Mehalel, Elchanan Mossel · 2026-06-16 04:00

ReLU网络在线可实现回归及其应用

arXiv:2602.19172v2 Announce Type: replace Abstract: Realizable online regression can behave very differently from online classification. Even without any margin or stochastic assumptions, realizability may enforce horizon-free (finite) cumulative loss under metric-like losses, ev…