English(EN) Measuring Differences between Conditional Distributions using Kernel Embeddings

新框架统一了用于条件分布比较的核嵌入方法

作者 PulseAugur 编辑部 · [3 个来源] · 2026-05-04 06:16

研究人员引入了一个名为条件最大均值差异（CMMD）的统一框架来测量条件分布之间的差异。该框架包括各种基于核的度量，例如 CMMD$_0$、CMMD$_1$ 和 CMMD$_2$，并提供了一个通用的 $s$ 级 CMMD。还提出了一种新颖的双重稳健估计器，如果至少一个底层模型被正确指定，该估计器将保持一致。论文通过数值实验表明，CMMD 在统计检验中能有效识别复杂的条件依赖关系。 AI

影响引入了一种分析条件分布的新统计方法，有可能改进机器学习中的模型评估和测试。

排序理由介绍新统计框架和估计器的学术论文。

在 arXiv stat.ML 阅读 →

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报道来源 [3]

Hugging Face Daily Papers TIER_1 English(EN) · 2026-05-04 06:16

使用核嵌入测量条件分布之间的差异

Comparing conditional distributions is a fundamental challenge in statistics and machine learning, with applications across a wide range of domains. While proposed methods for measuring discrepancies using kernel embeddings of distributions in a reproducing kernel Hilbert space (…
arXiv stat.ML TIER_1 English(EN) · Peter Moskvichev, Siu Lun Chau, Dino Sejdinovic · 2026-05-05 04:00

使用核嵌入测量条件分布之间的差异

arXiv:2605.02260v1 Announce Type: new Abstract: Comparing conditional distributions is a fundamental challenge in statistics and machine learning, with applications across a wide range of domains. While proposed methods for measuring discrepancies using kernel embeddings of distr…
arXiv stat.ML TIER_1 English(EN) · Dino Sejdinovic · 2026-05-04 06:16

使用核嵌入测量条件分布之间的差异

Comparing conditional distributions is a fundamental challenge in statistics and machine learning, with applications across a wide range of domains. While proposed methods for measuring discrepancies using kernel embeddings of distributions in a reproducing kernel Hilbert space (…

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报道来源 [3]

使用核嵌入测量条件分布之间的差异

使用核嵌入测量条件分布之间的差异

使用核嵌入测量条件分布之间的差异

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