1. MAML是什么? MAML,即Model-Agnostic Meta-Learning,是一种元学习算法,旨在通过少量训练样本快速适应新任务。MAML的关键思想是通过元学习优化模型参数,使其能够在遇到新任务时经过少量的梯度更新就能达到良好的性能。具体来说,MAML通过以下步骤进行训练: 元训练阶段: 在元训练阶段,MAML从多个任务中采样任务集。 对...
[论文精读] NIPS 2020 | Sharpened Generalization Bounds based on Conditional Mutual Information 人大高瓴GeWu-Lab https://gewu-lab.github.io/ 18 人赞同了该文章简介 这篇工作深入探讨了信息论与泛化能力之间的联系。考虑到互信息能够衡量两个随机变量间的统计相关性,本研究集中于分析输入(即训练集)与输出(...
Generalization Bounds 来自 Springer 喜欢 0 阅读量: 333 作者: M Reid 摘要: Inequalities; Sample complexity In the theory of statistical machine learning, a generalization bound – or, more precisely, a generalization error bound – is a statement about the predictive... 关键词: Quantitative ...
a网络语言具有比传统语言更大的开放性和自由度 The network language has compared to a traditional language bigger openness and the degree of freedom[translate] aBlack Anal Beauties 黑后门秀丽[translate] ato derive generalization bounds on the average error of T 正在翻译,请等待...[translate]...
Generalization Bound for Multiple Source Domain Adaptation To this end, we propose multisource domain adversarial networks (MDAN) that approach domain adaptation by optimizing task-adaptive generalization bounds. To ... H Zhao,S Zhang,G Wu,... 被引量: 0发表: 2018年 加载更多研究...
经验上来说，毫无疑问他们两者是存在联系的。体现的比较明显的领域在于弱监督学习（例如，半监督学习），...
这里As是指算法A在训练集s上面训练所得的hypothesis (predictor)。这个定义描述的就是，如果我们将Sample...
Finally, we employ these results in various contexts and derive generalization bounds for multi-index linear models, multi-class support vector machines, and K-means clustering for both hard and soft label setups, improving the known state-of-the-art rates. PDF Abstract ...
NeurIPS 2021 | Towards Sharper Generalization Bounds for Structured Prediction. 【编者按】本篇论文作者为李少杰、刘勇,通讯作者刘勇。论文被中国计算机学会(CCF)推荐的A类国际学术会议NeurIPS2021录用。NeurIPS是机器学习和计算神经科学领域的顶级国际会议。以下为论文详细解读。 引言 结构化预测涵盖了广泛的机器学习领域,...
The novel algorithm for linear SVM Regression(SVR) is proposed based on VC generalization bounds and applied to comprehensive development of county. 提出了基于VC推广界的线性支持向量机回归模型的新的构建算法,并应用于县域综合发展中,构建了邱县协调发展的经济计量模型,与传统的方法相比该算法效果更好且具有...