11 citations · 21 across the 19 of their papers we have counts for
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Trading off 1-norm and sparsity against rank for linear models using mathematical optimization: 1-norm minimizing partially reflexive ah-symmetric generalized inverses
Marcia Fampa, Jon Lee, Gabriel Ponte
The M-P (Moore-Penrose) pseudoinverse has as a key application the computation of least-squares solutions of inconsistent systems of linear equations. Irrespective of whether a giv…
1-norm minimization and minimum-rank structured sparsity for symmetric and ah-symmetric generalized inverses: rank one and two
Luze Xu, Marcia Fampa, Jon Lee
Generalized inverses are important in statistics and other areas of applied matrix algebra. A \emph{generalized inverse} of a real matrix is a matrix that satisfies the Moo…
An R Package for generating covariance matrices for maximum-entropy sampling from precipitation chemistry data
Hessa Al-Thani, Jon Lee
We present an open-source R package (MESgenCov v 0.1.0) for temporally fitting multivariate precipitation chemistry data and extracting a covariance matrix for use in the MESP (max…
Mixing convex-optimization bounds for maximum-entropy sampling
Zhongzhu Chen, Marcia Fampa, Amélie Lambert +1
The maximum-entropy sampling problem is a fundamental and challenging combinatorial-optimization problem, with application in spatial statistics. It asks to find a maximum-determin…
Experimental analysis of local searches for sparse reflexive generalized inverses
Marcia Fampa, Jon Lee, Gabriel Ponte +1
The well-known M-P (Moore-Penrose) pseudoinverse is used in several linear-algebra applications; for example, to compute least-squares solutions of inconsistent systems of linear e…