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Abstract : |
We discuss two types of algorithms for selecting relevant examples that have been developed in the context of computation learning theory. The examples are selected out of a stream of examples that are generated independently at random. The first two algorithms are the so-called "boosting" algorithms of Schapire [ Schapire, 1990] and Freund [ Freund, 1990] , and the Query-by-Committee algorithm of Seung [ Seung et al., 1992]. We describe the algorithms and some of their proven properties, point to some of their commonalities, and suggest some possible future implications., |
