118 citations · 146 across the 6 of their papers we have counts for
5 papers · 1 filter
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…
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…
Decision-Focused Learning: Through the Lens of Learning to Rank
Jayanta Mandi, Víctor Bucarey, Maxime Mulamba +1
In the last years decision-focused learning framework, also known as predict-and-optimize, have received increasing attention. In this setting, the predictions of a machine learnin…
Data Driven VRP: A Neural Network Model to Learn Hidden Preferences for VRP
Jayanta Mandi, Rocsildes Canoy, Víctor Bucarey +1
The traditional Capacitated Vehicle Routing Problem (CVRP) minimizes the total distance of the routes under the capacity constraints of the vehicles. But more often, the objective…
Contrastive Losses and Solution Caching for Predict-and-Optimize
Maxime Mulamba, Jayanta Mandi, Michelangelo Diligenti +3
Many decision-making processes involve solving a combinatorial optimization problem with uncertain input that can be estimated from historic data. Recently, problems in this class…