6 papers
Robust Low-Tubal-Rank Tensor Completion under Cross-Concentrated Sampling
HanQin Cai, Hanqin Cai, Longxiu Huang +2
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. Existin…
Robust Spectral Recovery for Dynamical Sampling
HanQin Cai, Longxiu Huang, Tianming Wang +1
We study the spectral recovery problem for dynamical sampling on a finite cyclic grid. Given time snapshots obtained from a fixed uniform spatial subsampling of the orbit $x_{\ell}…
Guarantees of a Preconditioned Subgradient Algorithm for Overparameterized Asymmetric Low-rank Matrix Recovery
Paris Giampouras, HanQin Cai, Rene Vidal
In this paper, we focus on a matrix factorization-based approach to recover low-rank {\it asymmetric} matrices from corrupted measurements. We propose an {\it Overparameterized Pre…
Property Inheritance for Subtensors in Tensor Train Decompositions
HanQin Cai, Longxiu Huang
Tensor dimensionality reduction is one of the fundamental tools for modern data science. To address the high computational overhead, fiber-wise sampled subtensors that preserve the…
Accelerating Ill-conditioned Hankel Matrix Recovery via Structured Newton-like Descent
HanQin Cai, Longxiu Huang, Xiliang Lu +1
This paper studies the robust Hankel recovery problem, which simultaneously removes the sparse outliers and fulfills missing entries from the partial observation. We propose a nove…
Three-dimensional signal processing: a new approach in dynamical sampling via tensor products
Yisen Wang, Hanqin Cai, Longxiu Huang
The dynamical sampling problem is centered around reconstructing signals that evolve over time according to a dynamical process, from spatial-temporal samples that may be noisy. Th…