On learning sets and functions
作者:B. K. Natarajan
摘要
This paper presents some results on the probabilistic analysis of learning, illustrating the applicability of these results to settings such as connectionist networks. In particular, it concerns the learning of sets and functions from examples and background information. After a formal statement of the problem, some theorems are provided identifying the conditions necessary and sufficient for efficient learning, with respect to measures of information complexity and computational complexity. Intuitive interpretations of the definitions and theorems are provided.
论文关键词:Learning sets, learning functions, probabilistic analysis, connectionist networks
论文评审过程:
论文官网地址:https://doi.org/10.1007/BF00114804