\advance\hsize by 1cm
\advance\vsize by 20pt
-\font\chapfont=csb14 at 16pt
\def\rawchapter#1{\vensure{0.5in}\bigskip\goodbreak
\leftline{\chapfont #1}
}
\endalgo
\thm
-The Contractive Bor\o{u}vka's algorithm finds the MST of the input graph in
-time $\O(\min(n^2,m\log n))$.
+The Contractive Bor\o{u}vka's algorithm finds the MST of the graph given as
+its input in time $\O(\min(n^2,m\log n))$.
We also show that this time bound is tight --- we construct an~explicit
family of graphs on which the algorithm spends $\Theta(m\log n)$ steps.
We recursively compute the MSF of those subgraphs and of the contracted graph. Then we take the
union of these MSF's and add the corrupted edges. According to the previous lemma, this does not produce
the MSF of~$G$, but a~sparser graph containing it, on which we can continue.
+%%The following theorem describes the properties of this partition:
\thmn{Partitioning to contractible clusters, Chazelle \cite{chazelle:almostacker}}\id{partthm}%
Given a~weighted graph~$G$ and parameters $\varepsilon$ ($0<\varepsilon\le 1/2$)
The Pettie's and Ramachandran's algorithm combines the idea of robust partitioning with optimal decision
trees constructed by brute force for very small subgraphs.
-Formally, the decision trees are defined as follows:
+%%Formally, the decision trees are defined as follows:
+Let us define them first:
\defnn{Decision trees and their complexity}\id{decdef}%
A~\df{MSF decision tree} for a~graph~$G$ is a~binary tree. Its internal vertices