Smoothed Analysis
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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Smoothed analysis is a way of measuring the complexity of an algorithm. It gives a more realistic analysis of the practical performance of the algorithm, such as its running time, than using worst-case or average-case scenarios. For instance the simplex algorithm runs in exponential-time in the worst-case and yet in practice it is a very efficient algorithm. This was one of the main motivations for developing smoothed analysis. Average-case analysis was first introduc...
Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Smoothed analysis is a way of measuring the complexity of an algorithm. It gives a more realistic analysis of the practical performance of the algorithm, such as its running time, than using worst-case or average-case scenarios. For instance the simplex algorithm runs in exponential-time in the worst-case and yet in practice it is a very efficient algorithm. This was one of the main motivations for developing smoothed analysis. Average-case analysis was first introduced to overcome the limitations of worst-case analysis, however the difficulty is saying what an average case is. The actual inputs and distribution of inputs may be different in practice from the assumptions made during the analysis.
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