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Merge pull request #227 from resibots/improve_doc [ci skip]
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Fixes in docs
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costashatz authored Jun 1, 2017
2 parents 364bcc5 + 5fd050e commit 69bf900
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2 changes: 1 addition & 1 deletion docs/guides/bo.rst
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Expand Up @@ -55,7 +55,7 @@ A GP is fully specified by its mean function :math:`\mu(\mathbf{x})` and covaria

.. math::
k_{SE}(\chi_1, \chi_2) = \sigma_f^2 \cdot \exp\left( \frac{\left|\left|\chi_1, \chi_2\right|\right|^2}{2 l^2} \right)
k_{SE}(\chi_1, \chi_2) = \sigma_f^2 \cdot \exp\left( -\frac{\left|\left|\chi_1 - \chi_2\right|\right|^2}{2 l^2} \right)
For some datasets, it makes sense to hand-tune these parameters (e.g., when there are very few samples). Ideally, our objective should be to learn :math:`l^2` (characteristic length scale) and :math:`\sigma_f^2` (overall variance).

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2 changes: 1 addition & 1 deletion src/limbo/kernel/exp.hpp
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Expand Up @@ -63,7 +63,7 @@ namespace limbo {
Exponential kernel (see :cite:`brochu2010tutorial` p. 9).
.. math::
k(v_1, v_2) = \sigma^2\exp \Big(-\frac{1}{l^2} ||v_1 - v_2||^2\Big)
k(v_1, v_2) = \sigma^2\exp \Big(-\frac{||v_1 - v_2||^2}{2l^2}\Big)
Parameters:
- ``double sigma_sq`` (signal variance)
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