Informally, a boosting technique is a method that, when applied to a particular class of algorithms, yields improved algorithms. The improvement must be provable and well defined in terms of one or more of the parameters characterizing the algorithmic performance. Examples of boosters can be found in the context of randomized algorithms (here, a booster allows one to turn a BPP algorithm into an RP one) and computational learning theory (here, a booster allows one to improve the prediction accuracy of a weak learning algorithm). The problem of compression boosting consists of designing a technique that improves the compression performance of a wide class of algorithms.
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