9 citations · 16 across the 12 of their papers we have counts for
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cs.LG2024
Low-Rank Tensor Learning by Generalized Nonconvex Regularization
Sijia Xia, Michael K. Ng, Xiongjun Zhang
In this paper, we study the problem of low-rank tensor learning, where only a few of training samples are observed and the underlying tensor has a low-rank structure. The existing…
cs.LG2022★ 2 cited
Noisy Nonnegative Tucker Decomposition with Sparse Factors and Missing Data
Xiongjun Zhang, Michael K. Ng
Tensor decomposition is a powerful tool for extracting physically meaningful latent factors from multi-dimensional nonnegative data, and has been an increasing interest in a variet…
cs.LG2019★ 9 cited
Robust Tensor Completion Using Transformed Tensor SVD
Guangjing Song, Michael K. Ng, Xiongjun Zhang
In this paper, we study robust tensor completion by using transformed tensor singular value decomposition (SVD), which employs unitary transform matrices instead of discrete Fourie…