1 citations · 1 across the 4 of their papers we have counts for
6 papers
Reward-Weighted Preference Optimization for Selective Combinatorial Optimization Problems
Haohui Zhang, Xinyu Hu, Wouter van Heeswijk +2
Reinforcement learning has emerged as an effective approach for combinatorial optimization, but most existing methods focus on problems such as the Travelling Salesperson Problem (…
RELAGRAM: Recursive Latent Graph Model for the Capacitated Vehicle Routing Problem
Vladimir Kirill Bickov, Neil Yorke-Smith
Latent recursion repeatedly processes internal representations through the same neural network. Recent work has shown this approach to be effective on structured reasoning tasks su…
Narcissus: Program Synthesis Using Context-Aware LLM Approximations
Tilman Hinnerichs, Sebastijan Dumancic, Neil Yorke-Smith
Large language models (LLMs) excel at programming, but not when the task fixes the target language: prompted with a grammar rare in their training data, their programs usually brea…
Deep Learning--Accelerated Multi-Start Large Neighborhood Search for Real-time Freight Bundling
Haohui Zhang, Wouter van Heeswijk, Xinyu Hu +2
Online Freight Exchange Systems (OFEX) play a crucial role in modern freight logistics by facilitating real-time matching between shippers and carrier. However, efficient combinato…
Modelling Program Spaces in Program Synthesis with Constraints
Tilman Hinnerichs, Bart Swinkels, Jaap de Jong +4
A core challenge in program synthesis is taming the large space of possible programs. Since program synthesis is essentially a combinatorial search, the community has sought to lev…
Mixed-Integer Optimisation of Graph Neural Networks for Computer-Aided Molecular Design
Tom McDonald, Calvin Tsay, Artur M. Schweidtmann +1
ReLU neural networks have been modelled as constraints in mixed integer linear programming (MILP), enabling surrogate-based optimisation in various domains and efficient solution o…