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Added bibliography entry for original ADMM paper

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Andreas Tsouchlos 2023-03-12 21:08:03 +01:00
parent c4dfcfbb24
commit 2f87165c0d
3 changed files with 16 additions and 5 deletions
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11
latex/thesis/bibliography.bib
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@ -121,3 +121,14 @@
doi={10.1109/TIT.2020.2984247}
}
@ARTICLE{original_admm,
author={Barman, Siddharth and Liu, Xishuo and Draper, Stark C. and Recht, Benjamin},
journal={IEEE Transactions on Information Theory},
title={Decomposition Methods for Large Scale LP Decoding},
year={2013},
volume={59},
number={12},
pages={7870-7886},
doi={10.1109/TIT.2013.2281372}
}

4
latex/thesis/chapters/decoding_techniques.tex
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@ -692,9 +692,9 @@ The resulting formulation of the relaxed optimization problem becomes:%
\begin{itemize}
\item Distributed nature, making it a competitor to BP
(which can also be implemented in a distributed manner)
(See original ADMM paper)
\cite[Sec. I]{original_admm}
\item Computational performance similar to BP has been demnonstrated
(See original ADMM paper)
\cite[Sec. I]{original_admm}
\end{itemize}
\item Adaptive linear programming?
\item How ADMM is adapted to LP decoding

6
latex/thesis/chapters/introduction.tex
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@ -6,10 +6,10 @@
\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 Error floor when decoding with BP (seems to not be persent with LP decoding
\cite[Sec. I]{original_admm})
\item Strong theoretical guarantees that allow for better and better approximations
for ML decoding (See original ADMM peper introduction)
for ML decoding \cite[Sec. I]{original_admm}
\end{itemize}
\item Results summary
\end{itemize}