Adaptive Weighted Nonnegative Matrix Factorization for Robust Feature Representation

1 code implementation • 7 Jun 2022 • Tingting Shen, Junhang Li, Can Tong, Qiang He, Chen Li, YuDong Yao, Yueyang Teng

Nonnegative matrix factorization (NMF) has been widely used to dimensionality reduction in machine learning.

Dimensionality Reduction

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