118 citations · 249 across the 32 of their papers we have counts for
7 papers · 1 filter
Preference Elicitation for Step-Wise Explanations in Logic Puzzles
Marco Foschini, Marianne Defresne, Emilio Gamba +2
Step-wise explanations can explain logic puzzles and other satisfaction problems by showing how to derive decisions step by step. Each step consists of a set of constraints that de…
Using Certifying Constraint Solvers for Generating Step-wise Explanations
Ignace Bleukx, Maarten Flippo, Bart Bogaerts +2
In the field of Explainable Constraint Solving, it is common to explain to a user why a problem is unsatisfiable. A recently proposed method for this is to compute a sequence of ex…
Feasibility-Aware Decision-Focused Learning for Predicting Parameters in the Constraints
Jayanta Mandi, Marianne Defresne, Senne Berden +1
When some parameters of a constrained optimization problem (COP) are uncertain, this gives rise to a predict-then-optimize (PtO) problem, comprising two stages: the prediction of t…
Minimizing Surrogate Losses for Decision-Focused Learning using Differentiable Optimization
Jayanta Mandi, Ali İrfan Mahmutoğulları, Senne Berden +1
Decision-focused learning (DFL) trains a machine learning (ML) model to predict parameters of an optimization problem, to directly minimize decision regret, i.e., maximize decision…
DCP-Bench-Open: Evaluating LLMs for Constraint Modelling of Discrete Combinatorial Problems
Kostis Michailidis, Dimos Tsouros, Tias Guns
Discrete Combinatorial Problems (DCPs) are prevalent in industrial decision-making and optimisation. However, while constraint solving technologies for DCPs have advanced significa…
Solver-Free Decision-Focused Learning for Linear Optimization Problems
Senne Berden, Ali İrfan Mahmutoğulları, Dimos Tsouros +1
Mathematical optimization is a fundamental tool for decision-making in a wide range of applications. However, in many real-world scenarios, the parameters of the optimization probl…