OpenAlex ·
Benign Overfitting Property of the Minimum $\ell_q$ -norm Interpolant Estimator in Regression Problem via Feature Space Decomposition
- Published
- Source
- OpenAlex
- Published in
- arXiv (Cornell University)
- DOI
- 10.48550/arxiv.2610.24350
- Original
- Read it at the publisher
- Topics
Abstract
This paper establishes high-probability, non-asymptotic upper bounds for the population excess risk of minimum $\ell_q$-norm interpolating estimators in linear regression, valid for all $1
The authors’ abstract, as arXiv lists it. arXiv’s listings, abstracts included, are free for anyone to reuse.
Read it on ReadSearch
Each opens after you create an account, and brings you back to this paper.
More in Artificial Intelligence
Dimension-free comparison inequalities between $f$-divergences for Gaussian location mixtures
On the skew-curvature power law relationship in a stochastic volatility model with infinite variation Lévy jumps
Exact probability laws of random inner products: Dirichlet splines, overlaps, uncertainty, and Bargmann invariants
Recursive Operator Localization and Spectral Gap Descent via the Geometry of Local Spectral Expansion
A discrete-continuous-time stochastic framework for attention-deficit/hyperactivity disorder-related symptom modeling and pharmacological intervention via methylphenidate
Get the few papers worth your time in Artificial Intelligence every morning.
ReadSearch reads the new papers in your field each day and brings you the few worth reading, each with its key finding in a sentence.