From 8ae85fd6b3649058da07b16c9ea139864c7f94a1 Mon Sep 17 00:00:00 2001 From: Rémi Flamary Date: Tue, 25 Jun 2019 14:57:26 +0200 Subject: alpha for documentation --- ot/gromov.py | 4 ++-- ot/unbalanced.py | 6 +++--- 2 files changed, 5 insertions(+), 5 deletions(-) (limited to 'ot') diff --git a/ot/gromov.py b/ot/gromov.py index cd961b0..3a7e24c 100644 --- a/ot/gromov.py +++ b/ot/gromov.py @@ -357,7 +357,7 @@ def fused_gromov_wasserstein(M, C1, C2, p, q, loss_fun='square_loss', alpha=0.5, Computes the FGW transport between two graphs see [24] .. math:: - \gamma = arg\min_\gamma (1-\alpha)*<\gamma,M>_F + \alpha* \sum_{i,j,k,l} + \gamma = arg\min_\gamma (1-\\alpha)*<\gamma,M>_F + \\alpha* \sum_{i,j,k,l} L(C1_{i,k},C2_{j,l})*T_{i,j}*T_{k,l} s.t. \gamma 1 = p @@ -440,7 +440,7 @@ def fused_gromov_wasserstein2(M, C1, C2, p, q, loss_fun='square_loss', alpha=0.5 Computes the FGW distance between two graphs see [24] .. math:: - \min_\gamma (1-\alpha)*<\gamma,M>_F + \alpha* \sum_{i,j,k,l} + \min_\gamma (1-\\alpha)*<\gamma,M>_F + \\alpha* \sum_{i,j,k,l} L(C1_{i,k},C2_{j,l})*T_{i,j}*T_{k,l} diff --git a/ot/unbalanced.py b/ot/unbalanced.py index 484ce95..bad12d6 100644 --- a/ot/unbalanced.py +++ b/ot/unbalanced.py @@ -19,7 +19,7 @@ def sinkhorn_unbalanced(a, b, M, reg, alpha, method='sinkhorn', numItermax=1000, The function solves the following optimization problem: .. math:: - W = \min_\gamma <\gamma,M>_F + reg\cdot\Omega(\gamma) + \alpha KL(\gamma 1, a) + \alpha KL(\gamma^T 1, b) + W = \min_\gamma <\gamma,M>_F + reg\cdot\Omega(\gamma) + \\alpha KL(\gamma 1, a) + \\alpha KL(\gamma^T 1, b) s.t. \gamma\geq 0 @@ -128,7 +128,7 @@ def sinkhorn_unbalanced2(a, b, M, reg, alpha, method='sinkhorn', The function solves the following optimization problem: .. math:: - W = \min_\gamma <\gamma,M>_F + reg\cdot\Omega(\gamma) + \alpha KL(\gamma 1, a) + \alpha KL(\gamma^T 1, b) + W = \min_\gamma <\gamma,M>_F + reg\cdot\Omega(\gamma) + \\alpha KL(\gamma 1, a) + \\alpha KL(\gamma^T 1, b) s.t. \gamma\geq 0 @@ -239,7 +239,7 @@ def sinkhorn_knopp_unbalanced(a, b, M, reg, alpha, numItermax=1000, The function solves the following optimization problem: .. math:: - W = \min_\gamma <\gamma,M>_F + reg\cdot\Omega(\gamma) + \alpha KL(\gamma 1, a) + \alpha KL(\gamma^T 1, b) + W = \min_\gamma <\gamma,M>_F + reg\cdot\Omega(\gamma) + \\alpha KL(\gamma 1, a) + \\alpha KL(\gamma^T 1, b) s.t. \gamma\geq 0 -- cgit v1.2.3