2 citations · 4 across the 4 of their papers we have counts for
4 papers
Scaling Decision-Focused Learning to Large Problems with Lagrangian Decomposition
Stéphane Eilles-Chan Way, Hugo Percot, Quentin Cappart +2
Decision-focused learning has shown great promise for addressing predict-then-optimize problems, particularly in the presence of under-specified models. However, its practical depl…
Learning Admissible Heuristics via Cost Partitioning
Hugo Barral, Quentin Cappart, Marie-José Huguet +1
Admissible heuristics are essential for optimal planning, yet learning them remains challenging due to the risk of overestimation. Cost partitioning combines multiple abstraction h…
Global Rewards in Multi-Agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systems
Heiko Hoppe, Tobias Enders, Quentin Cappart +1
We study vehicle dispatching in autonomous mobility on demand (AMoD) systems, where a central operator assigns vehicles to customer requests or rejects these with the aim of maximi…
On Causal Inference for Data-free Structured Pruning
Martin Ferianc, Anush Sankaran, Olivier Mastropietro +2
Neural networks (NNs) are making a large impact both on research and industry. Nevertheless, as NNs' accuracy increases, it is followed by an expansion in their size, required numb…