2.3.1 不可知的PAC Learning(Agnostic PAC Learning) 上面我们已经提到,在实践中,要达到Realizability Assumption实际上非常困难,不仅如此,在此前的讨论中我们假设样本的标签完全由输入的特征决定,但是实际上这也并不一定,例如,有可能存在两个木瓜的颜色和硬度都一模一样,但是味道大相径庭,因此不假设标签完全由输入元素...
As you know the PAC learnability is a concept in theoretical machine learning. Hence, it's a fundamental concept and mostly used in researches and proving some theorems. However, you can use from the bounds to estimate the size of training data and the accuracy of your learning methods in t...
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...
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,...
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...
这本书是对于想要知道ML更深的理论知识特别是statistical learning的一本必读书。不过里面的notation有的时候真的很乱。给出了不少平时不太会在别的书里看到的理论证明,比如PAC-Bayes Bounds,regularized risk minimization principle,非常elegant。而且经常会有定性和定量的两种讨论,对于理解这些理论很有帮助。
EXACT LOWER BOUNDS FOR THE AGNOSTIC PROBABLY-APPROXIMATELY-CORRECT (PAC) MACHINE LEARNING MODEL We provide an exact nonasymptotic lower bound on the minimax expected excess risk (EER) in the agnostic probably-approximately-correct (PAC) machine learni... API Kontorovich - 《Annals of Statistics An...
(2006). PAC-learning of Markov models with hidden state. In LNCS: Vol. 4212 . Proceedings of the European conference on machine learning ECML’06 (pp. 150–161). Berlin: Springer.R. Gavald`a, P. W. Keller, J. Pineau, and D. Precup. PAC-learning of Markov models with ...
In this article, PAC-learning theory is applied to model inference, which concerns the problem of inferring theories from facts in first order logic. It is argued that uniform sample PAC-learnabilityDOI: 10.1007/3-540-57868-4_60 被引量: 4 年份...
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...