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docs/source/quickstart.rst

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@@ -83,6 +83,29 @@ properties. It can computed from an already estimated OT matrix with
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Regularized Optimal Transport
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-----------------------------
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Recent developments have shown the interest of regularized OT both in terms of
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computational and statistical properties.
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We address in this section the regularized OT problem that can be expressed as
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.. math::
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\gamma^* = arg\min_\gamma <\gamma,M>_F + reg*\Omega(\gamma)
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s.t. \gamma 1 = a
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\gamma^T 1= b
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\gamma\geq 0
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where :
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- :math:`M\in\mathbb{R}_+^{m\times n}` is the metric cost matrix defining the cost to move mass from bin :math:`a_i` to bin :math:`b_j`.
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- :math:`a` and :math:`b` are histograms (positive, sum to 1) that represent the weights of each samples in the source an target distributions.
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- :math:`\Omega` is the regularization term.
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We disvuss in the following specific algorithms
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Entropic regularized OT
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^^^^^^^^^^^^^^^^^^^^^^^
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