118 citations · 144 across the 4 of their papers we have counts for
6 papers
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…
Score Function Gradient Estimation to Widen the Applicability of Decision-Focused Learning
Mattia Silvestri, Senne Berden, Jayanta Mandi +4
Many real-world optimization problems contain parameters that are unknown before deployment time, either due to stochasticity or to lack of information (e.g., demand or travel time…
Probability estimation and structured output prediction for learning preferences in last mile delivery
Rocsildes Canoy, Victor Bucarey, Yves Molenbruch +3
We study the problem of learning the preferences of drivers and planners in the context of last mile delivery. Given a data set containing historical decisions and delivery locatio…
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…
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…
Hybrid Classification and Reasoning for Image-based Constraint Solving
Maxime Mulamba, Jayanta Mandi, Rocsildes Canoy +1
There is an increased interest in solving complex constrained problems where part of the input is not given as facts but received as raw sensor data such as images or speech. We wi…