arXiv Machine Learning By Hanqin Cai, Longxiu Huang, Jing Qin, Chengyue Wu

Robust Low-Tubal-Rank Tensor Completion under Cross-Concentrated Sampling

Read the original on arXiv Machine Learning →

arXiv:2608. 03928v1 Announce Type: cross Abstract: Tensor cross-concentrated sampling (t-CCS) bridges entrywise sampling and t-CUR slice-wise sampling by observing entries only within selected horizontal and lateral slices.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

arXiv Statistics ML
Sep 22

Tensor Completion using Subspace Information

Tensor Completion using Subspace Information (TCSI) is an algorithm that leverages side information by estimating a subspace and reformulating tensor completion as a matrix regression problem. Theoretical analysis shows that accurate subspace information reduces sample complexity to nearly linear in the uncoupled ambient dimensions and relaxes signal-to-noise ratio requirements compared to existing guarantees. Numerical simulations and an application to reconstructing global Total Electron Content (TEC) maps demonstrate lower reconstruction errors than competing methods.

By Jingyang Li, Michael K. Ng
arXiv Statistics ML
2d ago

Casewise and Cellwise Robust Tensor-on-Tensor Regression

arXiv:2603.25911v2 Announce Type: replace-cross Abstract: Tensor-on-tensor regression is an important tool for the analysis of tensor data, aiming to predict a set of response tensors from a correspo...

By Mehdi Hirari, Fabio Centofanti, Mia Hubert, Stefan Van Aelst