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Add reference paper to the function hashing documentation.
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docs/src/function_hashing.md

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LSHFunctions can hash functions in any [``L^p_{\mu}(\Omega)`` function space](https://en.wikipedia.org/wiki/Lp_space) so long as ``\Omega`` has finite volume (i.e., as long as ``\int_{\Omega} d\mu(x) < +\infty``).
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## Similarity statistics in function spaces
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The LSHFunctions module currently supports the following similarity statistics for function spaces. Unless otherwise stated, all functions are assumed to be members of an [``L^p_{\mu}(\Omega)`` function space](https://en.wikipedia.org/wiki/Lp_space).
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The LSHFunctions module currently supports hashing for the following similarity statistics in function spaces.
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### ``L_{\mu}^p`` distance
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docs/src/glossary.md

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where ``\overline{g(x)}`` is the complex conjugate of ``g(x)``. A function in ``L^p_{\mu}(\Omega)`` must have the property that ``\|f\|_{L^p_{\mu}}`` is finite.
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*Example*: ``f(x) = x^2 - 3x + 2`` is a function in ``L^2([-1,1])`` (with ``\mu`` chosen to be [Lebesgue measure](https://en.wikipedia.org/wiki/Lebesgue_measure)) because ``\|f\|_{L^2} = \sqrt{\int_{-1}^1 \left|f(x)\right|^2 \hspace{0.15cm} dx}`` is finite. However, it is *not* a function in ``L^2([-\infty,\infty])`` because the ``\|f\|_{L^2} = \sqrt{\int_{-\infty}^{\infty} \left|f(x)\right|^2 \hspace{0.15cm} dx`` is infinite.
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*Example*: ``f(x) = x^2 - 3x + 2`` is a function in ``L^2([-1,1])`` (with ``\mu`` chosen to be [Lebesgue measure](https://en.wikipedia.org/wiki/Lebesgue_measure)) because ``\|f\|_{L^2} = \sqrt{\int_{-1}^1 \left|f(x)\right|^2 \hspace{0.15cm} dx}`` is finite. However, it is *not* a function in ``L^2([-\infty,\infty])`` because ``\|f\|_{L^2} = \sqrt{\int_{-\infty}^{\infty} \left|f(x)\right|^2 \hspace{0.15cm} dx}`` is infinite.
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docs/src/lshfunction_api.md

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## References
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- Shand, William and Becker, Stephen. *Locality-sensitive hashing in function spaces*. [arXiv:2002.03909](https://arxiv.org/abs/2002.03909).

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