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The Zero Pattern of a Design Matrix Drives Multiple Descent in Over-parameterized Regression

arxiv.org/abs/2607.24041

quality89

Updated 5 h ago · first seen 11 Sept 2026

paper_01M294FTBVHMYR127E1X1F8N4H

Published
11 Sept 2026
T1 · 5 h ago
arXiv
2607.24041
T1 · 5 h ago
Category
math.ST
T1 · 5 h ago

Abstract

-cross Abstract: Over-parameterized linear regression has been widely studied over the last decade. However, most existing works assume that the covariates are independent and that their covariance matrices are non-degenerate. In this paper, we relax both assumptions and derive deterministic equivalents for the prediction risk in a vanishing-ridge regime. We show that degeneracy of the covariance matrices and dependence can lead to multiple descent, and characterize where the corresponding peaks can occur. Our proofs use a novel graph representation of the variance profile. We show that maximum matchings and the Dulmage--Mendelsohn decomposition of the associated bipartite graph identify the configurations at which the variance becomes singular.

Authors 4

Kevin Han Huang, Haoyu Ye, Somak Laha, Morgane Austern

Specification

Official page

Source:arXiv (Atom API + RSS)T1observed 5 h agohigh

Arxiv announce type
replace

Source:arXiv (Atom API + RSS)T1observed 5 h agohigh

arXiv id
2607.24041

Source:arXiv (Atom API + RSS)T1observed 5 h agohigh

Categories
math.ST, cs.LG, stat.ML, stat.TH

Source:arXiv (Atom API + RSS)T1observed 5 h agohigh

PDF

Source:arXiv (Atom API + RSS)T1observed 5 h agohigh

Primary category
math.ST

Source:arXiv (Atom API + RSS)T1observed 5 h agohigh

Published
11 Sept 2026

Source:arXiv (Atom API + RSS)T1observed 5 h agohigh

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Provenance

Attributed facts

9

Source tiers

T19

Freshest observation

5 h ago

Conflicts

None