From 270483de67aecfe1fe8f697ad7f7cb5ebed84774 Mon Sep 17 00:00:00 2001 From: Manos Date: Thu, 14 Oct 2021 17:17:31 +0200 Subject: [PATCH] evaluation: Minor corrections --- text/evaluation/details.tex | 5 ++--- text/evaluation/theotherthing.tex | 2 +- 2 files changed, 3 insertions(+), 4 deletions(-) diff --git a/text/evaluation/details.tex b/text/evaluation/details.tex index fae9afe..e27fea9 100644 --- a/text/evaluation/details.tex +++ b/text/evaluation/details.tex @@ -1,4 +1,4 @@ -\section{Experimental setting and data sets} +\section{Setting, configurations, and data sets} \label{sec:eval-dtl} In this section we list all the relevant details regarding the evaluation setting (Section~\ref{subsec:eval-setup}), and we present the real and synthetic data sets that we used (Section~\ref{subsec:eval-dat}), along with the corresponding configurations (Section~\ref{subsec:eval-conf}). @@ -123,8 +123,7 @@ For this reason, and in order to create a more controlled environment for our ex We model the temporal correlation in the synthetic data as a \emph{stochastic matrix} $P$, using a \emph{Markov Chain}~\cite{gagniuc2017markov}. $P$ is an $n \times n$ matrix, where the element $P_{ij}$ %at the $i$th row of the $j$th column that -represents the transition probability from a state $i$ to another state $j$. -%, $\forall i, j \leq n$. +represents the transition probability from a state $i$ to another state $j$, $\forall$ $i$, $j$ $\leq$ $n$. It holds that the elements of every row $j$ of $P$ sum up to $1$. We follow the \emph{Laplacian smoothing} technique~\cite{sorkine2004laplacian}, as utilized in~\cite{cao2018quantifying}, to generate the matrix $P$ with a degree of temporal correlation $s > 0$ equal to % and generate a stochastic matrix $P$ with a degree of temporal correlation $s$ by calculating each element $P_{ij}$ as follows diff --git a/text/evaluation/theotherthing.tex b/text/evaluation/theotherthing.tex index 90cb20c..4ba8f9c 100644 --- a/text/evaluation/theotherthing.tex +++ b/text/evaluation/theotherthing.tex @@ -1,4 +1,4 @@ -\section{Selection of landmarks} +\section{Selection of {\thethings}} \label{sec:eval-lmdk-sel} In this section, we present the experiments on the methodology for the {\thething} selection presented in Section~\ref{subsec:lmdk-sel-sol}, on the real and synthetic data sets. With the experiments on the synthetic data sets (Section~\ref{subsec:sel-utl}) we show the normalized Euclidean and Wasserstein distance metrics (not to be confused with the temporal distances in Figure~\ref{fig:avg-dist})