In-place algorithm

Algorithms

In computer science, an in-place algorithm is an algorithm which transforms input using no auxiliary data structure. However, a small amount of extra storage space is allowed for auxiliary variables. The input is usually overwritten by the output as the algorithm executes. An in-place algorithm updates its input sequence only through replacement or swapping of elements. An algorithm which is not in-place is sometimes called not-in-place or out-of-place. In-place can have slightly different meanings. In its strictest form, the algorithm can only have a constant amount of extra space, counting everything including function calls and pointers. However, this form is very limited as simply having an index to a length n array requires O(log n) bits. More broadly, in-place means that the algorithm does not use extra space for manipulating the input but may require a small though nonconstant extra space for its operation. Usually, this space is O(log n), though sometimes anything in O(n) is allowed. Note that space complexity also has varied choices in whether or not to count the index lengths as part of the space used. Often, the space complexity is given in terms of the number of indices or pointers needed, ignoring their length. In this article, we refer to total space complexity (DSPACE), counting pointer lengths. Therefore, the space requirements here have an extra log n factor compared to an analysis that ignores the length of indices and pointers. An algorithm may or may not count the output as part of its space usage. Since in-place algorithms usually overwrite their input with output, no additional space is needed. When writing the output to write-only memory or a stream, it may be more appropriate to only consider the working space of the algorithm. In theoretical applications such as log-space reductions, it is more typical to always ignore output space (in these cases it is more essential that the output is write-only). (Wikipedia).

Build a Heap - Intro to Algorithms

This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.

From playlist Introduction to Algorithms

Centrality - Intro to Algorithms

This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.

From playlist Introduction to Algorithms

Heap Sort - Intro to Algorithms

This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.

From playlist Introduction to Algorithms

Graphing the system of two linear inequalities with two horizontal line

👉 Learn how to graph a system of inequalities. A system of inequalities is a set of inequalities which are collectively satisfied by a certain range of values for the variables. To graph a system of inequalities, each inequality making up the system is graphed individually with the side of

From playlist Solve a System of Inequalities by Graphing

Find the feasible region by graphing 4 linear inequalities

From playlist Solve a System of Inequalities by Graphing

Graphing a system of two inequalities in slope intercept form

From playlist Solve a System of Inequalities by Graphing

Graphing a system of two inequalities in slope intercept form

From playlist Solve a System of Inequalities by Graphing

Graphing a system of linear inequalities

From playlist Solve a System of Inequalities by Graphing

How to graph and shade a system of linear inequalities

From playlist Solve a System of Inequalities by Graphing

RailsConf 2017: Sorting Rubyists by Caleb Thompson

RailsConf 2017: Sorting Rubyists by Caleb Thompson Let's take a peek under the hood of the magical "sort" method, learning algorithms... by sorting audience members wearing numbers! Intimidated by the word "algorithm? Not sure what performance means? Confused by "Big O Notation"? Haven't

From playlist RailsConf 2017

Judicaël Courant : Affectation dans l’enseignement supérieur : sélection et algorithmes

Résumé : Déléguer à une machine l'affectation des bacheliers dans le supérieur pose un certain nombre de questions : quels règles souhaite-t-on pour l'accès au supérieur ? Quels sont alors les objectifs assignés à la machine ? Quel algorithme permet de les atteindre ? Comment permettre à t

From playlist Combinatorics

Frédéric Vivien : Ordonnancement - 2ème partie : ordonnancement sur machines parallèles

Find this video and other talks given by worldwide mathematicians on CIRM's Audiovisual Mathematics Library: http://library.cirm-math.fr. And discover all its functionalities: - Chapter markers and keywords to watch the parts of your choice in the video - Videos enriched with abstracts, b

From playlist Mathematical Aspects of Computer Science

Backtracking Algorithm | Introduction To Backtracking | Data Structures & Algorithms | Simplilearn

This video gives an introduction to backtracking that could help you prepare for competitive programming. This backtracking algorithm tutorial aims to help learn data structures and algorithms. This video will cover the following concepts: 00:00 Introduction to Backtracking Algorithm 0

From playlist Data Structures & Algorithms

Lec 20 | MIT RES.6-008 Digital Signal Processing, 1975

Lecture 20: Computation of the discrete Fourier transform, part 3 Instructor: Alan V. Oppenheim View the complete course: http://ocw.mit.edu/RES.6-008 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu

From playlist MIT RES.6-008 Digital Signal Processing, 1975

Bubble Sort Algorithm (Tutorial 2) D1 EDEXCEL A-Level

Powered by https://www.numerise.com/ This video is a tutorial on the Bubble Sort Algorithm for Decision 1 Math A-Level. Please make yourself revision notes while watching this and attempt my examples. Complete the suggested exercises from the Edexcel book. After this then move to my vid

From playlist Decision 1: Edexcel A-Level Maths Full Course

Haskell, Quicksort, and "In Place" Computations

Visit the Monday Morning Haskell blog! https://www.mmhaskell.com This video is our submission to the Summer of Math Exposition run by 3 Blue 1 Brown: https://www.3blue1brown.com/blog/some1 Check out their videos on YT: https://www.youtube.com/channel/UCYO_jab_esuFRV4b17AJtAw Huge thank

From playlist Summer of Math Exposition Youtube Videos

CSE 373 - Lecture 15, Fall 2020

From playlist CSE 373 -- Fall 2020

Lec 19 | MIT RES.6-008 Digital Signal Processing, 1975

Lecture 19: Computation of the discrete Fourier transform, part 2 Instructor: Alan V. Oppenheim View the complete course: http://ocw.mit.edu/RES.6-008 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu

From playlist MIT RES.6-008 Digital Signal Processing, 1975

Jana Cslovjecsek: Efficient algorithms for multistage stochastic integer programming using proximity

We consider the problem of solving integer programs of the form min {c^T x : Ax = b; x geq 0}, where A is a multistage stochastic matrix. We give an algorithm that solves this problem in fixed-parameter time f(d; ||A||_infty) n log^O(2d) n, where f is a computable function, d is the treed

From playlist Workshop: Parametrized complexity and discrete optimization

Richard Tsai: "Line-of-sight optimization for moving agents in complex urban domains"

Mathematical Challenges and Opportunities for Autonomous Vehicles 2020 Workshop I: Individual Vehicle Autonomy: Perception and Control "Line-of-sight optimization for moving agents in complex urban domains" Richard Tsai - University of Texas at Austin, Mathematics Abstract: I will presen

From playlist Mathematical Challenges and Opportunities for Autonomous Vehicles 2020

In-place algorithm

Related pages