An Algebraic-Geometric Approach for Linear Regression Without Correspondences

DOI10.1109/TIT.2020.2977166zbMath1446.62202arXiv1810.05440OpenAlexW3007679270MaRDI QIDQ5124491

Hayoung Choi, Liangzu Peng, Laurent Kneip, Yuanming Shi, Aldo Conca, Manolis C. Tsakiris

Publication date: 29 September 2020

Published in: IEEE Transactions on Information Theory (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1810.05440

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Linear regression; mixed models (62J05) Algebraic statistics (62R01)

Related Items (4)

Linear regression with partially mismatched data: local search with theoretical guarantees ⋮ Homomorphic sensing of subspace arrangements ⋮ Linear regression with mismatched data: a provably optimal local search algorithm ⋮ Unnamed Item

Uses Software

• Bertini
• CAP3
• SoftPOSIT
• Polyjam

This page was built for publication: An Algebraic-Geometric Approach for Linear Regression Without Correspondences