Linear Regression Without Correspondences via Concave Minimization
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2020.3019693
Abstract: Linear regression without correspondences concerns the recovery of a signal in the linear regression setting, where the correspondences between the observations and the linear functionals are unknown. The associated maximum likelihood function is NP-hard to… read more here.
Keywords: regression without; concave minimization; without correspondences; linear regression ... See more keywords
An Algebraic-Geometric Approach for Linear Regression Without Correspondences
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Information Theory"
DOI: 10.1109/tit.2020.2977166
Abstract: Linear regression without correspondences is the problem of performing a linear regression fit to a dataset for which the correspondences between the independent samples and the observations are unknown. Such a problem naturally arises in… read more here.
Keywords: regression; geometric approach; algebraic geometric; regression without ... See more keywords