13 citations · 16 across the 4 of their papers we have counts for
4 papers · 1 filter
When Deep Learning Meets Polyhedral Theory: A Survey
Joey Huchette, Gonzalo Muñoz, Thiago Serra +1
In the past decade, deep learning became the prevalent methodology for predictive modeling thanks to the remarkable accuracy of deep neural networks in tasks such as computer visio…
Exact reliability optimization for series-parallel graphs using convex envelopes
Javiera Barrera, Eduardo Moreno, Gonzalo Muñoz +1
Given its wide spectrum of applications, the classical problem of all-terminal network reliability evaluation remains a highly relevant problem in network design. The associated op…
Convex envelopes for ray-concave functions
Javiera Barrera, Eduardo Moreno, Gonzalo Muñoz
Convexification based on convex envelopes is ubiquitous in the non-linear optimization literature. Thanks to considerable efforts of the optimization community for decades, we are…
A study of the Bienstock-Zuckerberg algorithm, Applications in Mining and Resource Constrained Project Scheduling
Gonzalo Muñoz, Daniel Espinoza, Marcos Goycoolea +3
We study a Lagrangian decomposition algorithm recently proposed by Dan Bienstock and Mark Zuckerberg for solving the LP relaxation of a class of open pit mine project scheduling pr…