2 papers
cs.LG2025
Recurrent State Encoders for Efficient Neural Combinatorial Optimization
Tim Dernedde, Daniela Thyssens, Lars Schmidt-Thieme
The primary paradigm in Neural Combinatorial Optimization (NCO) are construction methods, where a neural network is trained to sequentially add one solution component at a time unt…
cs.LG2025
On Distributional Dependent Performance of Classical and Neural Routing Solvers
Daniela Thyssens, Tim Dernedde, Wilson Sentanoe +1
Neural Combinatorial Optimization aims to learn to solve a class of combinatorial problems through data-driven methods and notably through employing neural networks by learning the…