For this\npurpose, we employed the normalized volume element of the Bures (minimal\nmonotone) metric as a probability distribution over the fifteen-dimensional\nconvex set of 4 x 4 density matrices. Here, we provide further/independent\n(quasi-Monte Carlo numerical integration) evidence of a ...
How many miles to $\\beta\\omega$? -- Approximating $\\beta\\omega$ by metric-dependent compactifications 来自 arXiv.org 喜欢 0 阅读量: 63 作者:M Kada,K Tomoyasu,Y Yoshinobu 摘要: It is known that the Stone-\v{C}ech compactification $\stonecech{X}$ of a non-compact metrizable ...
TADAM: Task dependent adaptive metric for improved few-shot learningarxiv.org/abs/1805.10123 这篇paper主要关注了分类任务中,同一任务的多个类别之间有较强的相关性,从而根据任务中多个类别的共同特性对特征提取器进行调整。也就是小样本学习在图像识别领域的课题,目标在提高检测精度上。另外,文中也对常用的两...
An entropy formula for the heat equation on manifolds with time-dependent metric, application to ancient solutions - Guo, Philipowski, et al. () Citation Context ...iable and continuous in the second variable. This time-dependent stochastic differential equation has intrinsic links to non-linear...
metric度量中,欧式距离效果好于余弦距离 1.尺度scale the distance metric by a learnable temperatureα 交叉熵损失: 最小化同类别的距离,最大化非同类别的距离。相当于只学习hard sample 2. task conditioning feature extractorfϕ(·)to be task-dependentfϕ(X,Γ)...
A locally weighted normalized mutual information (wNMI) metric is proposed to highlight spatial correspondences in an image pair. Aiming to account for local similarities, our proposal computes the...doi:10.1007/978-3-319-19390-8_34M. Orbes-Arteaga...
aDespite the fact that the view-dependent error metric does not provide a guaranteed error bound, it is very efficient in practice and provides good terrain simplification while maintaining plausible visual results. 竟管看法依赖错误公尺不提供一个保证的错误区域,它实践上是非常高效率的并且提供好地形简单...
aTeam member: 队员:[translate] astart-up enterprise 起始的企业[translate] aNormal international (metric) drawing template. Uses Color Dependent Plot Styles. 正常国际 (公尺) 图画模板。 用途上色依赖剧情样式。[translate]
In this paper, an alternative metric addressing these drawbacks is introduced. The metric makes use of pre-characterized load dependent component models and estimates efficiency for arbitrary input data. The results are objectively comparable between different data center configurations as well as between...
Deep Metric Learning (DML) approaches learn to represent inputs to a lower-dimensional latent space such that the distance between representations in this space corresponds with a predefined notion of similarity. This paper investigates how the mapping element of DML may be exploited in situations ...