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20102026
most citedDecision-Focused Learning: Foundations, State of the Art, Benchmark and Future Opportunities

118 citations

Showing 2023Show all

5 papers · 1 filter

cs.LG2023★ 1 cited

Decision-focused predictions via pessimistic bilevel optimization: complexity and algorithms

Víctor Bucarey, Sophia Calderón, Gonzalo Muñoz +1

Dealing with uncertainty in optimization parameters is an important and longstanding challenge. Typically, uncertain parameters are predicted accurately, and then a deterministic o…

math.OC2023

The MIP Workshop 2023 Computational Competition on Reoptimization

Suresh Bolusani, Mathieu Besançon, Ambros Gleixner +5

This paper describes the computational challenge developed for a computational competition held in 2023 for the anniversary of the Mixed Integer Programming Work…

math.AP2023★ 1 cited

A relaxation approach to the minimisation of the neo-Hookean energy in 3D

Marco Barchiesi, Duvan Henao, Carlos Mora-Corral +1

Despite its high significance in nonlinear elasticity, the neo-Hookean energy is still not known to admit minimisers in some appropriate admissible class. Using ideas from relaxati…

cs.LG2023★ 118 cited

Decision-Focused Learning: Foundations, State of the Art, Benchmark and Future Opportunities

Jayanta Mandi, James Kotary, Senne Berden +4

Decision-focused learning (DFL) is an emerging paradigm that integrates machine learning (ML) and constrained optimization to enhance decision quality by training ML models in an e…

cs.RO2023★ 10 cited

An Open Source Design Optimization Toolbox Evaluated on a Soft Finger

Stefan Escaida Navarro, Tanguy Navez, Olivier Goury +2

In this paper, we introduce a novel open source toolbox for design optimization in Soft Robotics. We consider that design optimization is an important trend in Soft Robotics that i…