From 186f888e50c8b57b7654e095e457169b63b74bd8 Mon Sep 17 00:00:00 2001
From: Andrei Stoian <95410270+andrei-stoian-zama@users.noreply.github.com>
Date: Mon, 5 Sep 2022 14:02:26 +0200
Subject: [PATCH] chore: remove footnotes in doc (#1662)

---
 docs/advanced-topics/pruning.md | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/docs/advanced-topics/pruning.md b/docs/advanced-topics/pruning.md
index 006f43056..1ea4138ce 100644
--- a/docs/advanced-topics/pruning.md
+++ b/docs/advanced-topics/pruning.md
@@ -24,6 +24,4 @@ Fixing some of the weights to 0 makes the network graph look more similar to the
 
 ![Pruned Fully Connected Neural Network](../figures/prunednet.png)
 
-While pruning weights can reduce the prediction performance of the neural network, studies show that a high level of pruning (above 50% \[^1\]) can often be applied. See here how Concrete-ML uses pruning in [Fully Connected Neural Networks](../_apidoc/concrete.ml.sklearn.html#concrete.ml.sklearn.qnn.NeuralNetClassifier).
-
-\[^1\]: Han, Song & Pool, Jeff & Tran, John & Dally, William. (2015). Learning both Weights and Connections for Efficient Neural Networks.
+While pruning weights can reduce the prediction performance of the neural network, studies show that a high level of pruning (above 50%) can often be applied. See here how Concrete-ML uses pruning in [Fully Connected Neural Networks](../_apidoc/concrete.ml.sklearn.html#concrete.ml.sklearn.qnn.NeuralNetClassifier).