Not surely consistent: learning problem is difficult or contains noises, can't guarantee∀S∼Dm,∃hS,R^S(hS)=0 fromFoundations of Machine Learning: 这种情况下, 我们还是有双侧 Chernoff Bound:PS∼Dm[|R^S(h)−R(h)|≥ϵ]≤2exp(−2mϵ2) ...
Understanding Machine Learning(2): PAC Learning Metoo 被统计和机器学习耽误了的非传统商科生观前提醒 作者为初学者,本文仅为读书笔记,仅供参考,文章可能存在大量错误和叙述不清楚的地方,请在评论区指出,谢谢!文章参考教材:Understanding Machine Learning: From Theory to Algorithms by Shai Shalev-Shwartz and...
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...
Sign in Sign up pacjn / machine-learning-yearning-cn forked from deeplearning-ai/machine-learning-yearning-cn Watch 1 Star 0 Fork 1.4k Code Pull requests Actions Projects Security Insights master machine-learning-yearning-cn
机器学习基础链接 Foundations of machine learning, M.Mohri, A.Rostamizadeh, A.Talwalkar模型选择 ERM 算法集寻找误差的最优解, hSERM=argminh∈HR^S(h),h_S^{ERM} = \arg\min_{h\in H} \hat{R}_S(h), hSERM=argh∈HminR^S(h), 未必会成功, 因为忽略了假设 hhh 的复杂...
【后现代贝叶斯机器学习(Post-Bayesian Machine Learning)】 01:11:42 【数学教授修投影屏幕(Math Professor Fixes Projector Screen)】 02:48 【牛顿-皮普斯问题: 牛顿错了?】 10:13 【《我的世界》极低概率事件:一个人能有多幸运】 24:29 【我是如何对科学家失去信任的】 10:25 【构建谷歌的软件...
Machine LearningBy a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators discuss new findings in artificial intelligence. According to news originatingfrom Oulu, Finland, by NewsRx editors, the research stated, "The application of machine learning models...
In: IEEE Int. Conf. on Acoustics,Speech and Signal Processing. ICASSP,pp. 708 712. Fu,S.-W.,Hu,T.-y.,Tsao,Y.,Lu,X.,2017a. Complex spectrogram enhancement by convolutional neural network with multi-metrics learning. In: Int. Workshop on Machine Learning for Signal Processing. MLSP,...
We define this learning m... D Haussler,M Warmuth - Springer US 被引量: 40发表: 1993年 Exact Lower Bounds for the Agnostic Probably-Approximately-Correct (PAC) Machine Learning Model We provide an exact non-asymptotic lower bound on the minimax expected excess risk (EER) in the agnostic ...
In this work, we propose the first – to the best of our knowledge – Pac-Bayes generalization bounds for classifiers trained on data exhibiting interdependencies. The approach undertaken to establish our results is based on the decomposition of a so-called dependency graph that encodes the ...