Recognition: unknown
The smallest singular value of a random rectangular matrix
classification
🧮 math.PR
math.FA
keywords
matrixsingularsmallestvalueestimateprobabilityrandomsqrt
read the original abstract
We prove an optimal estimate on the smallest singular value of a random subgaussian matrix, valid for all fixed dimensions. For an N by n matrix A with independent and identically distributed subgaussian entries, the smallest singular value of A is at least of the order \sqrt{N} - \sqrt{n-1} with high probability. A sharp estimate on the probability is also obtained.
This paper has not been read by Pith yet.
Forward citations
Cited by 1 Pith paper
-
Sharp Capacity Scaling of Spectral Optimizers in Learning Associative Memory
Muon achieves higher storage capacity than SGD and matches Newton's method in one-step recovery rates for associative memory under power-law distributions, while saturating at larger critical batch sizes and showing f...
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.