English(EN) Learning-augmented smooth integer programs with PAC-learnable oracles

新的LEAP框架通过学习增强布尔多项式优化

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-14 05:00

研究人员开发了LEAP，一个用于平滑整数规划的新框架，这是布尔多项式优化问题的广泛类别。这个端到端的学习增强系统使用在采样实例上训练的预言机来预测未见问题的布尔赋值。LEAP然后围绕预测的赋值线性化目标，解决一个有误差预算的线性规划，并对分数解进行四舍五入，提供近似损失和PAC风格学习的保证。 AI

影响该框架可以提高解决各个领域复杂优化问题的效率和可扩展性。

排序理由该集群包含一篇详细介绍新计算框架的学术论文。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.AI 阅读 →

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Newsworthiness bucket: Tool; 该集群包含一篇详细介绍新计算框架的学术论文。[lever_c_demoted from research: ic=1 ai=0.7]
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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Hao-Yuan He, Jiang-Tian Xue, Ming Li, Zhi-Hua Zhou · 2026-11-14 05:00

具有PAC可学预言机的学习增强平滑整数规划

arXiv:2602.02505v2 Announce Type: replace-cross Abstract: We study an end-to-end learning-augmented framework for smooth integer programs, a broad class of Boolean polynomial optimization problems including MAX-CUT and MAX-k-SAT. An oracle learned from sampled instances predicts …

本文如何被排名

报道来源 [1]

具有PAC可学预言机的学习增强平滑整数规划

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