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In computer science, a stable sorting algorithm preserves the order of records with equal keys. In numerical analysis, a numerically stable algorithm avoids magnifying small errors. An algorithm is stable if the result produced is relatively insensitive to perturbations during computation.
The "slide" analogy is a reference to the slide projector, a device that has become somewhat obsolete due to the use of presentation software. Slides can be printed, or (more usually) displayed on-screen and navigated through at the command of the presenter. An entire presentation can be saved in video format. [6]
A stable learning algorithm would produce a similar classifier with both the 1000-element and 999-element training sets. Stability can be studied for many types of learning problems, from language learning to inverse problems in physics and engineering, as it is a property of the learning process rather than the type of information being learned.
This algorithm is guaranteed to produce a stable marriage for all participants in time where is the number of men or women. [11] Among all possible different stable matchings, it always yields the one that is best for all men among all stable matchings, and worst for all women. [12]
Computer programming or coding is the composition of sequences of instructions, called programs, that computers can follow to perform tasks. [1] [2] It involves designing and implementing algorithms, step-by-step specifications of procedures, by writing code in one or more programming languages.
This is a list of algorithm general topics. Analysis of algorithms; Ant colony algorithm; ... Sorting algorithm; Search algorithm; Stable algorithm (disambiguation)
Stable sorting algorithms maintain the relative order of records with equal keys (i.e. values). That is, a sorting algorithm is stable if whenever there are two records R and S with the same key and with R appearing before S in the original list, R will appear before S in the sorted list.
An early example of answer set programming was the planning method proposed in 1997 by Dimopoulos, Nebel and Köhler. [3] [4] Their approach is based on the relationship between plans and stable models. [5] In 1998 Soininen and Niemelä [6] applied what is now known as answer set programming to the problem of product configuration. [4]