Improving Generalization with Active Learning

作者:David Cohn, Les Atlas, Richard Ladner

摘要

Active learning differs from “learning from examples” in that the learning algorithm assumes at least some control over what part of the input domain it receives information about. In some situations, active learning is provably more powerful than learning from examples alone, giving better generalization for a fixed number of training examples.

论文关键词:queries, active learning, generalization, version space, neural networks

论文评审过程:

论文官网地址:https://doi.org/10.1023/A:1022673506211