References etc.

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Antti H S Laaksonen 2017-02-25 21:47:47 +02:00
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@ -359,7 +359,8 @@ The expected value for $X$ in a geometric distribution is
\index{Markov chain}
A \key{Markov chain} is a random process
A \key{Markov chain}\footnote{A. A. Markov (1856--1922)
was a Russian mathematician.} is a random process
that consists of states and transitions between them.
For each state, we know the probabilities
for moving to other states.
@ -516,7 +517,9 @@ It turns out that we can find order statistics
using a randomized algorithm without sorting the array.
The algorithm is a Las Vegas algorithm:
its running time is usually $O(n)$
but $O(n^2)$ in the worst case.
but $O(n^2)$ in the worst case\footnote{C. A. R. Hoare
discovered both this algorithm, known as \key{quickselect} \cite{hoa61b},
and a similar sorting algorithm, known as \key{quicksort} \cite{hoa61a}.}.
The algorithm chooses a random element $x$
in the array, and moves elements smaller than $x$
@ -561,7 +564,8 @@ answer would by easier than to calculate it from scratch.
It turns out that we can solve the problem
using a Monte Carlo algorithm whose
time complexity is only $O(n^2)$.
time complexity is only $O(n^2)$\footnote{This algorithm is sometimes
called \index{Freivalds' algoritm} \key{Freivalds' algorithm} \cite{fre77}.}.
The idea is simple: we choose a random vector
$X$ of $n$ elements, and calculate the matrices
$ABX$ and $CX$. If $ABX=CX$, we report that $AB=C$,

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@ -248,7 +248,8 @@ and this is always the final state.
It turns out that we can easily classify
any nim state by calculating
the \key{nim sum} $x_1 \oplus x_2 \oplus \cdots \oplus x_n$,
where $\oplus$ is the xor operation.
where $\oplus$ is the xor operation\footnote{The optimal strategy
for nim was published in 1901 by C. L. Bouton \cite{bou01}}.
The states whose nim sum is 0 are losing states,
and all other states are winning states.
For example, the nim sum for
@ -367,7 +368,8 @@ so the nim sum is not 0.
\index{SpragueGrundy theorem}
The \key{SpragueGrundy theorem} generalizes the
The \key{SpragueGrundy theorem}\footnote{The theorem was discovered
independently by R. Sprague \cite{spr35} and P. M. Grundy \cite{gru39}} generalizes the
strategy used in nim to all games that fulfil
the following requirements:

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@ -35,6 +35,11 @@
\emph{Programming Pearls}.
Addison-Wesley, 1986.
\bibitem{bou01}
C. L. Bouton.
Nim, a game with a complete mathematical theory.
\emph{Annals of Mathematics}, 3(1/4):35--39, 1901.
\bibitem{cod15}
Codeforces: On ''Mo's algorithm'',
\url{http://codeforces.com/blog/entry/20032}
@ -94,6 +99,11 @@
Maximal flow through a network.
\emph{Canadian Journal of Mathematics}, 8(3):399--404, 1956.
\bibitem{fre77}
R. Freivalds.
Probabilistic machines can use less running time.
In \emph{IFIP congress}, 839--842, 1977.
\bibitem{gal14}
F. Le Gall.
Powers of tensors and fast matrix multiplication.
@ -116,6 +126,11 @@
\emph{2014 IEEE 55th Annual Symposium on Foundations of Computer Science},
621--630, 2014.
\bibitem{gru39}
P. M. Grundy.
Mathematics and games.
\emph{Eureka}, 2(5):6--8, 1939.
\bibitem{gus97}
D. Gusfield.
\emph{Algorithms on Strings, Trees and Sequences:
@ -139,6 +154,16 @@
Über die Möglichkeit, einen Linienzug ohne Wiederholung und ohne Unterbrechung zu umfahren.
\emph{Mathematische Annalen}, 6(1), 30--32, 1873.
\bibitem{hoa61a}
C. A. R. Hoare.
Algorithm 64: Quicksort.
\emph{Communications of the ACM}, 4(7):321, 1961.
\bibitem{hoa61b}
C. A. R. Hoare.
Algorithm 65: Find.
\emph{Communications of the ACM}, 4(7):321--322, 1961.
\bibitem{hop71}
J. E. Hopcroft and J. D. Ullman.
A linear list merging algorithm.
@ -231,6 +256,11 @@
A strong-connectivity algorithm and its applications in data flow analysis.
\emph{Computers \& Mathematics with Applications}, 7(1):67--72, 1981.
\bibitem{spr35}
R. Sprague.
Über mathematische Kampfspiele.
\emph{Tohoku Mathematical Journal}, 41:438--444, 1935.
\bibitem{sta06}
P. Stańczyk.
\emph{Algorytmika praktyczna w konkursach Informatycznych},