3 papers
math.NA2024
Tensor Deli: Tensor Completion for Low CP-Rank Tensors via Random Sampling
Cullen Haselby, Mark Iwen, Santhosh Karnik +1
We propose two provably accurate methods for low CP-rank tensor completion - one using adaptive sampling and one using nonadaptive sampling. Both of our algorithms combine matrix c…
cs.IT2023
Fast and Low-Memory Compressive Sensing Algorithms for Low Tucker-Rank Tensor Approximation from Streamed Measurements
Cullen Haselby, Mark A. Iwen, Deanna Needell +2
In this paper we consider the problem of recovering a low-rank Tucker approximation to a massive tensor based solely on structured random compressive measurements. Crucially, the p…
math.NA2023
Tensor Sandwich: Tensor Completion for Low CP-Rank Tensors via Adaptive Random Sampling
Cullen Haselby, Santhosh Karnik, Mark Iwen
We propose an adaptive and provably accurate tensor completion approach based on combining matrix completion techniques (see, e.g., arXiv:0805.4471, arXiv:1407.3619, arXiv:1306.297…