Questions tagged [kernel-mean-embedding]

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On the choice of kernel in HSIC dependence measure

It is necessary to choose a kernel to use HSIC measure for dependence detection between two distributions, in a sensitivity analysis context for example. Among them, using universal kernel is ...
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Information preserved in the kernel mean embedding

I have recently been introduced to the kernel mean embedding of distributions, that is the map $$\mu: \mathcal{M}^{1}_{+}(X) \rightarrow \mathcal{H} \\ \mu(P) := \int \phi(x) dP(x)$$ where $K$ is a ...
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How to solve Error in lme? [closed]

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Kernel Mean Embedding relationship to regular kernel functions

I am struggling to understand kernel mean embeddings and how it relates to typical kernel functions. Review of Kernel Basics: Basically, a kernel function maps points (or vectors) from one feature ...
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Maximum Mean Discrepancy Implementation

I am just beginning to learn about MMD as a way to measure the difference between two probability distributions using this tutorial. I want to implement it code-wise but I don't understand it ...
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Earth Movers Distance and Maximum Mean Discrepency

By Kantorovich-Rubinstein duality the Earth Movers Distance (EMD)/Wasserstein Metric is equivalent to Maximum Mean Discrepancy (MMD) correct? See here for a more thorough explanation. Why then does ...
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