2 citations · 2 across the 22 of their papers we have counts for
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Computing Experiment-Constrained D-Optimal Designs
Aditya Pillai, Gabriel Ponte, Marcia Fampa +3
In optimal experimental design, the objective is to select a limited set of experiments that maximizes information about unknown model parameters based on factor levels. This work…
ADMM for 0/1 D-optimality and Maximum-Entropy Sampling Relaxations
Gabriel Ponte, Marcia Fampa, Jon Lee +1
The 0/1 D-optimality problem and the Maximum-Entropy Sampling problem are two well-known NP-hard discrete maximization problems in experimental design. Algorithms for exact optimiz…
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…