学习有没有一个综合性的模型指导(Is there a general model of learning)? PAC学习框架(Probably Approximately Correct learning framework)可以解释上述问题。 (The PAC framework helps define the class of learnable concepts in terms of the number of sample points needed to achieve an approximate solution,...
对于简单的问题(如Learning axis-aligned rectangles)可以直接使用PAC理论证明其是可学习的,但对于大多数问题,只能给出定性的分析。 概率上界 PAC理论指出学习的关键是 PS∼DN[R^S(h)≤ϵ]≥1−δ⇔R(h)≈0 实际泛化误差R(h)无法直接获得,但根据大数定律,当样本量N足够大时,经验误差和泛化误差趋于相等...
定义1.3 PAC-学习(PAC-learning):我们说一个概念集合 C 是PAC可学习的,当且仅当存在一个算法 $\mathcal{A}$ 以及一个多项式函数 $poly(\cdot,\cdot,\cdot,\cdot)$,使得对任意的 $\epsilon > 0$ 和 $\delta > 0$ 对所有在 $\mathcal{X}$ 上的分布 $D$,以及对所有的目标概念 $c \in C$,当...
PAC-Bayesian Machine Learning: Learning by Optimizing a Performance GuaranteeMario Marchand
Foundations of Machine Learning: The PAC Learning Framework(2) Foundations of Machine Learning: The PAC Learning Framework(2)(一)假设集有限在一致性下的学习界。在上一篇文章中我们介绍了PAC-learnable的定义,以及证明了一个例子是PAC-learnable。 这一节我们介绍当hypothesis set是有限时,且算法AA相对与样本...
tional complexity, no model-free algorithm has been proven to be PAC-MDP. In this paper, we present a new model-free algorithm, Delayed Q-learning, and prove it is the first such algorithm. The hardness of learning an arbitrary MDP as mea- sured by sample complexity is still relatively...
PAC学习 机器学习paclearning 写在最前:本系列主要是在阅读 Mehryar Mohri 等的最新书籍《Foundations of Machine Learning》以及 Schapire 和 Freund 的《Boosting: Foundations and Algorithms》过程中所做的笔记。主要讨论三个部分的内容。第一部分是PAC的基本概念,介绍了泛化误差和经验误差,并且讨论了假设集$H$有限...
” Thus, in this example, each concept is a thing. To model this learning task, we have to convert “real things” intomathematical descriptions of things. One possibility to do this is to fix some language to express afinitelist of properties. Afterward, we decide which of these ...
模型学习(Modellearning)是一种通过系统的输入输出观察来对系统进行自动化形式建模的方法,通过自动化学习目标系统的形式化模型以补充测试和验证技术。目前,模型学习已经成功应用到很多工业领域,也正在成为一种高效的漏洞寻找技术。 在1987年,Angluin提出了著名的L * 算法,该方法提供了一个正则语言的主动模型学习(Active...
Probably Approximately Correct (PAC) learning analyzes machine learning mathematically using probability bounds.