diff --git a/latex/thesis/chapters/decoding_techniques.tex b/latex/thesis/chapters/decoding_techniques.tex
index 25d9820..b9e0c36 100644
--- a/latex/thesis/chapters/decoding_techniques.tex
+++ b/latex/thesis/chapters/decoding_techniques.tex
@@ -689,6 +689,13 @@ The resulting formulation of the relaxed optimization problem becomes:%
 
 \begin{itemize}
     \item Why ADMM?
+        \begin{itemize}
+            \item Distributed nature, making it a competitor to BP
+                (which can also be implemented in a distributed manner)
+                (See original ADMM paper)
+            \item Computational performance similar to BP has been demnonstrated
+                (See original ADMM paper)
+        \end{itemize}
     \item Adaptive linear programming?
     \item How ADMM is adapted to LP decoding
 \end{itemize}
diff --git a/latex/thesis/chapters/introduction.tex b/latex/thesis/chapters/introduction.tex
index 91c251e..011116b 100644
--- a/latex/thesis/chapters/introduction.tex
+++ b/latex/thesis/chapters/introduction.tex
@@ -5,6 +5,12 @@
 \begin{itemize}
     \item Problem definition
     \item Motivation
+        \begin{itemize}
+            \item Error floor when decoding with BP (seems to not be persent with LP decoding - 
+                see original ADMM paper introduction)
+            \item Strong theoretical guarantees that allow for better and better approximations
+                for ML decoding (See original ADMM peper introduction)
+        \end{itemize}
     \item Results summary
 \end{itemize}