A Review of Some Extensions to the PAC Learning Model

作者: Sanjeev R. Kulkarni

DOI: 10.1007/978-1-4612-4088-4_3

关键词:

摘要: The Probably Approximately Correct (PAC) learning model, which has received much attention recently in the machine community, attempts to formalize notion of from examples. In this paper, we review several extensions basic PAC model with a focus on information complexity learning. discussed are over class distributions, queries, functions, and generalized samples.

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