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Given functions $f,g: \mathcal{X} \to \mathcal{H}$ lying in a vector-valued RKHS $\mathcal{H}_v$, i.e. outputting functions in the RKHS $\mathcal{H}$, what can we do about bounding the quantity

$$ \mathbb{E}_{x \sim \mathbb{P}_X}\left[ \langle f(x), g(x) \rangle_{\mathcal{H}} \right] $$

using Cauchy-Schwarz.

Do we have something like:

$$ \mathbb{E}_{x \sim \mathbb{P}_X}\left[ \langle f(x), g(x) \rangle_{\mathcal{H}} \right] \le \sqrt{\mathbb{E}_{x \sim \mathbb{P}_X}\left[ \Vert f(x) \Vert_{\mathcal{H}}^2 \right]\mathbb{E}_{x \sim \mathbb{P}_X}\left[ \Vert g(x) \Vert_{\mathcal{H}}^2 \right]} $$

What can we say about

$$ \mathbb{E}_{x \sim \mathbb{P}_X}\left[ h(x) \Vert f(x) - g(x) \Vert_{\mathcal{H}}^2 \right] $$

for some some function $h:\mathcal{X} \to \mathbb{R}$?

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  • $\begingroup$ Looks like Cauchy-Schwarz in $L^2(\mathcal X; \mathcal H)$. $\endgroup$ Commented Feb 21 at 16:35
  • $\begingroup$ i.e. like math.stackexchange.com/questions/684982/… but with the measure replaced by the probability measure? $\endgroup$ Commented Feb 22 at 19:42
  • $\begingroup$ yes, that should work $\endgroup$ Commented Feb 22 at 21:11
  • $\begingroup$ Great, thank you! $\endgroup$ Commented Feb 22 at 21:28

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