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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 ...
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 .
In this randomized algorithm, if . Compared to weighted algorithm, this randomness halved the number of mistakes the algorithm is going to make. [ 9 ] However, it is important to note that in some research, people define η = 1 / 2 {\displaystyle \eta =1/2} in weighted majority algorithm and allow 0 ≤ η ≤ 1 {\displaystyle 0\leq \eta \leq 1 ...
Monte Carlo methods in finance are often used to evaluate investments in projects at a business unit or corporate level, or other financial valuations. They can be used to model project schedules, where simulations aggregate estimates for worst-case, best-case, and most likely durations for each task to determine outcomes for the overall ...
The List Update or the List Access problem is a simple model used in the study of competitive analysis of online algorithms.Given a set of items in a list where the cost of accessing an item is proportional to its distance from the head of the list, e.g. a linked List, and a request sequence of accesses, the problem is to come up with a strategy of reordering the list so that the total cost of ...
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).
Average-case analysis requires a notion of an "average" input to an algorithm, which leads to the problem of devising a probability distribution over inputs. Alternatively, a randomized algorithm can be used. The analysis of such algorithms leads to the related notion of an expected complexity. [2]: 28
An analysis of the capacities, the contract or agreement, and the relationship between collaborating stakeholders is conducted. Analysis of contracting-out and/or collaborations can ensure goals are met successfully prior to the beginning of a partnership, and correct inefficiencies throughout the time frame of the collaboration.