activity
20162026
most citedWhen Deep Learning Meets Polyhedral Theory: A Survey

13 citations · 16 across the 4 of their papers we have counts for

collaborators

5 papers

cs.DS2026

Fair Online Resource Allocation

Christopher En, Yuri Faenza, Andrea Lodi +1

We study the problem of fair online resource allocation, motivated by applications such as refugee resettlement and airline scheduling, where agents arrive sequentially and must be…

math.OC2023★ 13 cited

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…

math.OC2021★ 2 cited

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…

math.OC2021★ 1 cited

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…

math.OC2016

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…