11 citations · 21 across the 19 of their papers we have counts for
20 papers
Convex relaxation for the generalized maximum-entropy sampling problem
Gabriel Ponte, Marcia Fampa, Jon Lee
The generalized maximum-entropy sampling problem (GMESP) is to select an order- principal submatrix from an order- covariance matrix, to maximize the product of its great…
Good and Fast Row-Sparse ah-Symmetric Reflexive Generalized Inverses
Gabriel Ponte, Marcia Fampa, Jon Lee +1
We present several algorithms aimed at constructing sparse and structured sparse (row-sparse) generalized inverses, with application to the efficient computation of least-squares s…
On computing sparse generalized inverses
Gabriel Ponte, Marcia Fampa, Jon Lee +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…
Computing D-Optimal solutions for huge-scale linear and quadratic response-surface models
Gabriel Ponte, Marcia Fampa, Jon Lee
We consider algorithmic approaches to the D-optimality problem for cases where the input design matrix is large and highly structured, in particular implicitly specified as a full…
Branch-and-bound for integer D-Optimality with fast local search and variable-bound tightening
Gabriel Ponte, Marcia Fampa, Jon Lee
We develop a branch-and-bound algorithm for the integer D-optimality problem, a central problem in statistical design theory, based on two convex relaxations, employing variable-bo…
Generalized Scaling for the Constrained Maximum-Entropy Sampling Problem
Zhongzhu Chen, Marcia Fampa, Jon Lee
The best practical techniques for exact solution of instances of the constrained maximum-entropy sampling problem, a discrete-optimization problem arising in the design of experime…