4 citations · 4 across the 1 of their papers we have counts for
4 papers
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…
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…
Preference Elicitation for Multi-objective Combinatorial Optimization with Active Learning and Maximum Likelihood Estimation
Marianne Defresne, Jayanta Mandi, Tias Guns
Real-life combinatorial optimization problems often involve several conflicting objectives, such as price, product quality and sustainability. A computationally-efficient way to ta…
Minimizing Surrogate Losses for Decision-Focused Learning using Differentiable Optimization
Jayanta Mandi, Ali Ä°rfan MahmutoÄulları, 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…