diff --git a/main.tex b/main.tex
index d86b59a26b85c0d09222a8392d82e1dbbfd2fe3b..d8748c174a45f2aa426c5e22e704707230c668e9 100644
--- a/main.tex
+++ b/main.tex
@@ -257,6 +257,8 @@ We solve this problem by decoupling the gradient averaging from the weight avera
 
 \subsection{MNIST and Linear Model}
 
+% To regenerate the figure, from directory results/mnist
+% python ../../../learn-topology/tools/plot_convergence.py 1-node-iid/all/2021-03-10-09:20:03-CET fully-connected/all/2021-03-10-09:25:19-CET clique-ring/all/2021-03-10-10:15:24-CET fully-connected-cliques/all/2021-03-10-10:19:44-CET --add-min-max --yaxis validation-accuracy --labels '1-node IID bsz=12800' '100-nodes non-IID fully-connected bsz=128' '100-nodes non-IID D-Clique (Ring)' '100-nodes non-IID D-Cliques (Fully-Connected)' --legend 'lower right' --ymin 80 --ymax 92.5
      \begin{figure}[htbp]
          \centering
          \includegraphics[width=0.7\textwidth]{figures/10-cliques-validation-accuracy}
diff --git a/results/mnist/clique-ring/experiments.sh b/results/mnist/clique-ring/experiments.sh
index 65e7e7ae0f4ec6bde913f8a773cf6e429ed59ffb..18b67d89b2a6fbd2709cc7caedfd2683c099b07a 100755
--- a/results/mnist/clique-ring/experiments.sh
+++ b/results/mnist/clique-ring/experiments.sh
@@ -8,7 +8,7 @@ LRS='
     '
 for BSZ in $BSZS; 
     do for LR in $LRS;
-        do python sgp-mnist.py --nb-nodes 100 --nb-epochs 100 --local-classes 1 --seed 1 --nodes-per-class 10 10 10 10 10 10 10 10 10 10 --global-train-ratios 0.802568 0.802568 0.802568 0.802568 0.802568 0.802568 0.802568 0.802568 0.802568 0.802568 --dist-optimization d-psgd --topology fully-connected-cliques --metric dissimilarity --learning-momentum 0. --sync-per-mini-batch 1 --results-directory $CWD/all --learning-rate $LR --batch-size $BSZ "$@" --parallel-training --nb-workers 10 --dataset mnist --model linear --clique-gradient --initial-averaging
+        do python sgp-mnist.py --nb-nodes 100 --nb-epochs 100 --local-classes 1 --seed 1 --nodes-per-class 10 10 10 10 10 10 10 10 10 10 --global-train-ratios 0.802568 0.802568 0.802568 0.802568 0.802568 0.802568 0.802568 0.802568 0.802568 0.802568 --dist-optimization d-psgd --topology clique-ring --metric dissimilarity --learning-momentum 0. --sync-per-mini-batch 1 --results-directory $CWD/all --learning-rate $LR --batch-size $BSZ "$@" --parallel-training --nb-workers 10 --dataset mnist --model linear --clique-gradient --initial-averaging
     done;
 done;