Subspace Nonnegative Matrix Factorization for Feature Representation

1 code implementation • 18 Apr 2022 • Junhang Li, Jiao Wei, Can Tong, Tingting Shen, Yuchen Liu, Chen Li, Shouliang Qi, YuDong Yao, Yueyang Teng

Traditional nonnegative matrix factorization (NMF) learns a new feature representation on the whole data space, which means treating all features equally.

An Entropy Weighted Nonnegative Matrix Factorization Algorithm for Feature Representation

1 code implementation • 27 Nov 2021 • Jiao Wei, Can Tong, Bingxue Wu, Qiang He, Shouliang Qi, YuDong Yao, Yueyang Teng

Nonnegative matrix factorization (NMF) has been widely used to learn low-dimensional representations of data.

Attribute