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  2. Randomized algorithm - Wikipedia

    en.wikipedia.org/wiki/Randomized_algorithm

    A randomized algorithm is an algorithm that employs a degree of randomness as part of its logic or procedure. The algorithm typically uses uniformly random bits as an auxiliary input to guide its behavior, in the hope of achieving good performance in the "average case" over all possible choices of random determined by the random bits; thus either the running time, or the output (or both) are ...

  3. Yao's principle - Wikipedia

    en.wikipedia.org/wiki/Yao's_principle

    Here, a Las Vegas algorithm is a randomized algorithm whose runtime may vary, but for which the result is always correct. [ 7 ] [ 8 ] For example, this form of Yao's principle has been used to prove the optimality of certain Monte Carlo tree search algorithms for the exact evaluation of game trees .

  4. Category:Randomized algorithms - Wikipedia

    en.wikipedia.org/wiki/Category:Randomized_algorithms

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  5. Multiplicative weight update method - Wikipedia

    en.wikipedia.org/wiki/Multiplicative_Weight...

    Then, there might be a tie. Following the weight update rule in weighted majority algorithm, the predictions made by the algorithm would be randomized. The algorithm calculates the probabilities of experts predicting positive or negatives, and then makes a random decision based on the computed fraction: [further explanation needed] predict

  6. Monte Carlo algorithm - Wikipedia

    en.wikipedia.org/wiki/Monte_carlo_algorithm

    In computing, a Monte Carlo algorithm is a randomized algorithm whose output may be incorrect with a certain (typically small) probability. Two examples of such algorithms are the Karger–Stein algorithm [ 1 ] and the Monte Carlo algorithm for minimum feedback arc set .

  7. Las Vegas algorithm - Wikipedia

    en.wikipedia.org/wiki/Las_vegas_algorithm

    Las Vegas algorithms were introduced by László Babai in 1979, in the context of the graph isomorphism problem, as a dual to Monte Carlo algorithms. [3] Babai [4] introduced the term "Las Vegas algorithm" alongside an example involving coin flips: the algorithm depends on a series of independent coin flips, and there is a small chance of failure (no result).

  8. Probabilistic analysis of algorithms - Wikipedia

    en.wikipedia.org/wiki/Probabilistic_analysis_of...

    It starts from an assumption about a probabilistic distribution of the set of all possible inputs. This assumption is then used to design an efficient algorithm or to derive the complexity of a known algorithm. This approach is not the same as that of probabilistic algorithms, but the two may be combined.

  9. Algorithm engineering - Wikipedia

    en.wikipedia.org/wiki/Algorithm_engineering

    The 1997 Workshop on Algorithm Engineering (WAE'97) was held in Venice (Italy) on September 11–13, 1997. The Third International Workshop on Algorithm Engineering (WAE'99) was held in London, UK in July 1999. [6] The first Workshop on Algorithm Engineering and Experimentation (ALENEX99) was held in Baltimore, Maryland on January 15–16, 1999 ...