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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. Random optimization - Wikipedia

    en.wikipedia.org/wiki/Random_optimization

    The basic RO algorithm can then be described as: Initialize x with a random position in the search-space. Until a termination criterion is met (e.g. number of iterations performed, or adequate fitness reached), repeat the following: Sample a new position y by adding a normally distributed random vector to the current position x

  4. Category:Randomized algorithms - Wikipedia

    en.wikipedia.org/wiki/Category:Randomized_algorithms

    Main page; Contents; Current events; Random article; About Wikipedia; Contact us

  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. Stochastic optimization - Wikipedia

    en.wikipedia.org/wiki/Stochastic_optimization

    swarm algorithms; evolutionary algorithms. genetic algorithms by Holland (1975) [19] evolution strategies; cascade object optimization & modification algorithm (2016) [20] In contrast, some authors have argued that randomization can only improve a deterministic algorithm if the deterministic algorithm was poorly designed in the first place. [21]

  8. Linear parameter-varying control - Wikipedia

    en.wikipedia.org/wiki/Linear_parameter-varying...

    For example, in case of aircraft control, a set of controllers are designed at different gridded locations of corresponding parameters such as AoA, Mach, dynamic pressure, CG etc. In brief, gain scheduling is a control design approach that constructs a nonlinear controller for a nonlinear plant by patching together a collection of linear ...

  9. BPP (complexity) - Wikipedia

    en.wikipedia.org/wiki/BPP_(complexity)

    A Monte Carlo algorithm is a randomized algorithm which is likely to be correct. Problems in the class BPP have Monte Carlo algorithms with polynomial bounded running time. This is compared to a Las Vegas algorithm which is a randomized algorithm which either outputs the correct answer, or outputs "fail" with low probability.