2)我新写的拆解、统一partialFC分类和样本infonce的方法,可以借鉴这个做修改了。 3)这种方法,本质上是norm以后,消除了W和feature的范数尺度带来的影响,让模型均衡的对待两个模态。 换一个角度来思考,模态学习的速度,占优和不占优,是不是也是在norm值的大小上体现出来? 4)进一步思考,现在是均衡的对待两种模态,如...
It's an unknown function handle put in by the user but my function had issues with calculating the euclidian Norm of a vector when theres cosine or sine in it, that's why I used the example. I solved it by a simple workaround: ...
Informational content of cosine and other similarities calculated from high-dimensional Conceptual Property Norm dataCosine similarityEuclidean distanceChebyshev distanceClusteringConceptual propertiesTo study concepts that are coded in language, researchers often collect lists of conceptual properties produced by ...
In this paper, we provide an analysis of the existing two-stage representation learning framework for the few-shot object detection from the perspective of normalization in the latent space, which is achieved by delving into cosine, thereby exploring the intrinsic reason behind its promotion of the...
The method uses an L, optimality norm. To achieve a better approximating effect, a new modulating function which compresses the oscillations of the cosine is proposed. A parameter sets the gradient of the modulating function, with respect to the oscillations' compression. The approximating ...
The nonuniform version of L1 formula is employed for approximating the Caputo fractional derivative, and a cosine pseudo-spectral approximation is utilized in spatial discretization. With the help of discrete fractional Gronwall inequality and global consistency analysis, sharp H-1-norm error estimate ...
SIGNAL PROCESSING -AMSTERDAM-ApostolovP.Peter Apostolov, Method for FIR filters design with compressed cosine using Chebyshev's norm, Signal Processing, v.91 n.11, p.2589-2594, November, 2011 [doi>10.1016/j.sigpro.2011.05.014]