理学 学习理论 释 PAC learning PAC学习 PAC (Probably Approximately Correct)学习，中文翻译为概率近似正确学习，是计算学习理论中最重要的研究内容之一，由图灵奖得主Valiant [1]于1984年首先提出的学习框架。PAC学习给出了一种数学形式化刻画机器学习的框架，基于此框架，很多学习问题得以从理论上进一步探讨，如什么样的学习任务是可以学习的。
人工智能 机器学习 释文 probably approximately correct learning 概率近似正确学习
- non-orientable development
- non-orientable manifold
- nonorientable manifold
- non-orientable polyhedron
- non-orientable surface
- non-oriented
- non-oriented cobordism
- non-oriented graph
- non-oriented silicon steel
- non-oriented surface
- non-orthogonal
- non-orthogonal expansion
- non-orthogonal factors
- non-oscillation
- non-oscillation interval
- non-oscillatory
- non-oscillatory and non-free-parameter dissipation difference scheme
- non-overlapping
- nonoverlapping domain decomposition method
- non-overlapping intervals
- non-overlapping sets
- non-overload design
- non oxide ceramic fuel
- non-oxide ceramic fuel
- nonoxide ceramic fuel