2024年10月4日 · To uncover the statistical structures of such data, we propose Functional Singular Value Decomposition (FSVD), a unified framework encompassing various tasks for …

The code in this repository demonstrates the application of our proposed FSVD methodology to various tasks, such as optimal dimension reduction, functional clustering, functional …

Figure 1: A pictorial illustration of FSVD: images on the horizontal (x-y) plane represent the FSVD of irregularly observed functional data, while the curves along the vertical (z)

The code in this repository demonstrates the application of our proposed FSVD methodology to various tasks, such as optimal dimension reduction, functional clustering, functional …

Heterogeneous functional data are commonly seen in time series and longitudinal data analysis. To capture the statistical structures of such data, we propose the framework of Functional …

This codebase contains TensorFlow implementation of Functional SVD, an SVD routine that accepts objects with 3 attributes: dot, T, and shape. The object must be able to exactly …

2020年2月18日 · FunkSVD就是在SVD的技术上优化“数据稠密”+“计算复杂度告”+“只可以用来数据降维”难题的。 一个矩阵做SVD分解成3个矩阵很耗时，同时还面临稀疏的问题，那么解决稀 …

2024年7月3日 · FSVD for a pair of dense or sparse functional data. Ly1, Lt1, Ly2, Lt2, FPCAoptns1 = NULL, FPCAoptns2 = NULL, SVDoptns = list() A list of n vectors containing the …

1.1 Related Work The framework of FSVD connects to a broad range of literature in functional data anal-ysis, PCA, and SVD. PCA and SVD versus Functional PCA and Functional SVD.

2021年8月29日 · FunkSVD方法是Simon Funk在Netflix电影推荐比赛中使用并取得良好效果，因此得名。 那么怎么得到矩阵P和Q呢？ 这里巧妙地利用了优化的思想： 以一个 实际例子 进行说 …