1 citations · 1 across the 3 of their papers we have counts for
6 papers
On the column number and forbidden submatrices for -modular matrices
Joseph Paat, Ingo Stallknecht, Zach Walsh +1
An integer matrix is -modular if the determinant of each submatrix of has absolute value at mo…
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…
Gaining or Losing Perspective for Piecewise-Linear Under-Estimators of Convex Univariate Functions
Jon Lee, Daphne Skipper, Emily Speakman +1
We study MINLO (mixed-integer nonlinear optimization) formulations of the disjunction , where is a binary indicator of (),…
Improving proximity bounds using sparsity
Jon Lee, Joseph Paat, Ingo Stallknecht +1
We refer to the distance between optimal solutions of integer programs and their linear relaxations as proximity. In 2018, Eisenbrand and Weismantel proved that proximity is indepe…
Approximate 1-norm minimization and minimum-rank structured sparsity for various generalized inverses via local search
Luze Xu, Marcia Fampa, Jon Lee +1
Fundamental in matrix algebra and its applications, a \emph{generalized inverse} of a real matrix is a matrix that satisfies the Moore-Penrose (M-P) property . If $H…
More Virtuous Smoothing
Luze Xu, Jon Lee, Daphne Skipper
In the context of global optimization of mixed-integer nonlinear optimization formulations, we consider smoothing univariate functions that satisfy , is increasing…