English(EN) Two-Sided Nearest Neighbors: An adaptive and minimax optimal procedure for matrix completion

新的双边最近邻算法增强了矩阵补全

作者 PulseAugur 编辑部 · [1 个来源] · 2026-08-26 04:00

研究人员开发了一种新颖的双边最近邻（NN）算法，旨在改进矩阵补全，特别是在具有非平滑、非线性数据和大量缺失条目的情况下。这种自适应程序实现了 minimax 最优性，意味着其性能在某些条件下理论上是最优的。该算法的均方误差（MSE）会适应底层非线性的平滑度，即使在许多矩阵条目确定性缺失的情况下也能提供有意义的结果。研究结果得到了数值模拟和使用 HeartSteps 移动健康研究数据的案例研究的支持。 AI

影响这项研究为处理复杂数据集中的缺失数据提供了一种更稳健的方法，有可能改进推荐系统和顺序决策模型。

排序理由关于矩阵补全新算法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv stat.ML 阅读 →

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报道来源 [1]

arXiv stat.ML TIER_1 English(EN) · Tathagata Sadhukhan, Manit Paul, Raaz Dwivedi · 2026-08-26 04:00

双面最近邻：一种自适应且 minimax 最优的矩阵补全方法

arXiv:2411.12965v3 Announce Type: replace Abstract: Nearest neighbor (NN) algorithms have been extensively used for missing data problems in recommender systems and sequential decision-making systems. Prior theoretical analysis has established favorable guarantees for NN when the…

本文如何被排名

报道来源 [1]

双面最近邻：一种自适应且 minimax 最优的矩阵补全方法

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