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  2. No free lunch in search and optimization - Wikipedia

    en.wikipedia.org/wiki/No_free_lunch_in_search...

    Each search algorithm performs well on almost all objective functions. [11] So if one is not concerned with the "relatively small" differences between search algorithms, e.g., because computer time is cheap, then you shouldn't worry about no free lunch. An algorithm may outperform another on a problem when neither is specialized to the problem.

  3. List of algorithms - Wikipedia

    en.wikipedia.org/wiki/List_of_algorithms

    An algorithm is fundamentally a set of rules or defined procedures that is typically designed and used to solve a specific problem or a broad set of problems.. Broadly, algorithms define process(es), sets of rules, or methodologies that are to be followed in calculations, data processing, data mining, pattern recognition, automated reasoning or other problem-solving operations.

  4. Algorithm - Wikipedia

    en.wikipedia.org/wiki/Algorithm

    Flowchart of using successive subtractions to find the greatest common divisor of number r and s. In mathematics and computer science, an algorithm (/ ˈ æ l ɡ ə r ɪ ð əm / ⓘ) is a finite sequence of mathematically rigorous instructions, typically used to solve a class of specific problems or to perform a computation. [1]

  5. Outline of computer science - Wikipedia

    en.wikipedia.org/wiki/Outline_of_computer_science

    Computer vision – Algorithms for identifying three-dimensional objects from a two-dimensional picture. Soft computing , the use of inexact solutions for otherwise extremely difficult problems: Machine learning - Development of models that are able to learn and adapt without following explicit instructions, by using algorithms and statistical ...

  6. Introduction to Algorithms - Wikipedia

    en.wikipedia.org/wiki/Introduction_to_Algorithms

    Introduction to Algorithms is a book on computer programming by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein. The book is described by its publisher as "the leading algorithms text in universities worldwide as well as the standard reference for professionals". [ 1 ]

  7. Algorithms for calculating variance - Wikipedia

    en.wikipedia.org/wiki/Algorithms_for_calculating...

    This algorithm can easily be adapted to compute the variance of a finite population: simply divide by n instead of n − 1 on the last line.. Because SumSq and (Sum×Sum)/n can be very similar numbers, cancellation can lead to the precision of the result to be much less than the inherent precision of the floating-point arithmetic used to perform the computation.

  8. Duality (optimization) - Wikipedia

    en.wikipedia.org/wiki/Duality_(optimization)

    In mathematical optimization theory, duality or the duality principle is the principle that optimization problems may be viewed from either of two perspectives, the primal problem or the dual problem.

  9. Greedy algorithm - Wikipedia

    en.wikipedia.org/wiki/Greedy_algorithm

    Greedy algorithms determine the minimum number of coins to give while making change. These are the steps most people would take to emulate a greedy algorithm to represent 36 cents using only coins with values {1, 5, 10, 20}. The coin of the highest value, less than the remaining change owed, is the local optimum.

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