Wasserstein Nonnegative Tensor Factorization with Manifold Regularization

no code implementations • 3 Jan 2024 • Jianyu Wang, Linruize Tang

Nonnegative tensor factorization (NTF) has become an important tool for feature extraction and part-based representation with preserved intrinsic structure information from nonnegative high-order data.

Robust Manifold Nonnegative Tucker Factorization for Tensor Data Representation

no code implementations • 8 Nov 2022 • Jianyu Wang, Linruize Tang, Jie Chen, Jingdong Chen

Nonnegative Tucker Factorization (NTF) minimizes the euclidean distance or Kullback-Leibler divergence between the original data and its low-rank approximation which often suffers from grossly corruptions or outliers and the neglect of manifold structures of data.