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The analyses of many algorithms and data structures (such as digital search trees) for searching and sorting are based on the representation of the keys involved as bit strings and so count the number of bit comparisons. On the other hand,…

Probability · Mathematics 2012-02-14 James Allen Fill , Svante Janson

When the search algorithm QuickSelect compares keys during its execution in order to find a key of target rank, it must operate on the keys' representations or internal structures, which were ignored by the previous studies that quantified…

Probability · Mathematics 2012-09-24 James Allen Fill , Takehiko Nakama

The Quickselect algorithm (also called FIND) is a fundamental algorithm for selecting ranks or quantiles within a set of data. Gr\"ubel and R\"osler showed that the number of key comparisons required by Quickselect considered as a process…

Probability · Mathematics 2024-12-31 Jasper Ischebeck , Ralph Neininger

In this note the precise minimum number of key comparisons any dual-pivot quickselect algorithm (without sampling) needs on average is determined. The result is in the form of exact as well as asymptotic formul\ae{} of this number of a…

Combinatorics · Mathematics 2016-10-18 Daniel Krenn

Sorting algorithms have attracted a great deal of attention and study, as they have numerous applications to Mathematics, Computer Science and related fields. In this thesis, we first deal with the mathematical analysis of the Quicksort…

Data Structures and Algorithms · Computer Science 2015-10-05 Vasileios Iliopoulos

In this paper, we analyse the dual pivot Quicksort, a variant of the standard Quicksort algorithm, in which two pivots are used for the partitioning of the array. We are solving recurrences of the expected number of key comparisons and…

Data Structures and Algorithms · Computer Science 2015-03-31 Vasileios Iliopoulos , David B. Penman

Most previous studies of the sorting algorithm QuickSort have used the number of key comparisons as a measure of the cost of executing the algorithm. Here we suppose that the n independent and identically distributed (i.i.d.) keys are each…

Probability · Mathematics 2013-03-14 James Allen Fill

We consider a multi-pivot QuickSort algorithm using $K\in\mathbb{N}$ pivot elements to partition a nonsorted list into $K+1$ sublists in order to proceed recursively on these sublists. For the partitioning stage, various strategies are in…

Probability · Mathematics 2026-05-01 Cecilia Holmgren , Jasper Ischebeck , Daniel Krenn , Florian Lesny , Ralph Neininger

There is excitement within the algorithms community about a new partitioning method introduced by Yaroslavskiy. This algorithm renders Quicksort slightly faster than the case when it runs under classic partitioning methods. We show that…

Data Structures and Algorithms · Computer Science 2014-11-18 Sebastian Wild , Markus E. Nebel , Hosam Mahmoud

We present an average case analysis of a variant of dual-pivot quicksort. We show that the used algorithmic partitioning strategy is optimal, i.e., it minimizes the expected number of key comparisons. For the analysis, we calculate the…

This work presents a comparison for the performance of sequential sorting algorithms under four different modes of execution, the sequential processing mode, a conventional multi-threading implementation, multi-threading with OpenMP Library…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-09-07 Mohammad Fasha

We provide a smoothed analysis of Hoare's find algorithm and we revisit the smoothed analysis of quicksort. Hoare's find algorithm - often called quickselect - is an easy-to-implement algorithm for finding the k-th smallest element of a…

Data Structures and Algorithms · Computer Science 2009-04-27 Mahmoud Fouz , Manfred Kufleitner , Bodo Manthey , Nima Zeini Jahromi

The complexity of the Quicksort algorithm is usually measured by the number of key comparisons used during its execution. When operating on a list of $n$ data, permuted uniformly at random, the appropriately normalized complexity $Y_n$ is…

Probability · Mathematics 2013-01-25 Ralph Neininger

A common problem in machine learning is to rank a set of n items based on pairwise comparisons. Here ranking refers to partitioning the items into sets of pre-specified sizes according to their scores, which includes identification of the…

Machine Learning · Computer Science 2018-01-08 Reinhard Heckel , Max Simchowitz , Kannan Ramchandran , Martin J. Wainwright

This paper gives a straightforward self-contained proof of the formula for the variance of the number of comparisons used by the Quicksort sorting algorithm when pivots are chosen uniformly at random. The result has been known for some time…

Probability · Mathematics 2010-06-22 Vasileios Iliopoulos , David Penman

We show that several versions of Floyd and Rivest's algorithm Select for finding the $k$th smallest of $n$ elements require at most $n+\min\{k,n-k\}+o(n)$ comparisons on average and with high probability. This rectifies the analysis of…

Data Structures and Algorithms · Computer Science 2007-05-23 Krzysztof C. Kiwiel

Smoothed analysis is a framework for analyzing the complexity of an algorithm, acting as a bridge between average and worst-case behaviour. For example, Quicksort and the Simplex algorithm are widely used in practical applications, despite…

Machine Learning · Computer Science 2015-03-29 Bichen Shi , Michel Schellekens , Georgiana Ifrim

We show that several versions of Floyd and Rivest's algorithm Select for finding the $k$th smallest of $n$ elements require at most $n+\min\{k,n-k\}+o(n)$ comparisons on average and with high probability. This rectifies the analysis of…

Data Structures and Algorithms · Computer Science 2007-05-23 Krzysztof C. Kiwiel

Given $n$ elements, an integer $k$ and a parameter $\varepsilon$, we study to select an element with rank in $(k-n\varepsilon,k+n\varepsilon]$ using unreliable comparisons where the outcome of each comparison is incorrect independently with…

Data Structures and Algorithms · Computer Science 2022-05-04 Shengyu Huang , Chih-Hung Liu , Daniel Rutschman

We investigate distributed memory parallel sorting algorithms that scale to the largest available machines and are robust with respect to input size and distribution of the input elements. The main outcome is that four sorting algorithms…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-01-17 Michael Axtmann , Peter Sanders
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