2 citations · 2 across the 9 of their papers we have counts for
5 papers · 1 filter
Annealed Sinkhorn with Momentum: Certified Unregularized Optimal Transport in Linear Memory
Samuel J. K. Chin, Maximilian Schiffer
We characterize Bregman Douglas-Rachford splitting (BDRS) for unregularized discrete optimal transport and develop an anytime primal-dual certificate in linear memory. We first est…
Neural Cluster First, Route Second: Capacitated Vehicle Routing via Differentiable Optimal Transport
Samuel J. K. Chin, Maximilian Schiffer
The Capacitated Vehicle Routing Problem (CVRP) underpins modern last-mile logistics, where routing decisions recur over the same fixed service area, like a city. In this setting, r…
Linear Decision Tree Policies for Integer Linear Programs
Théo Guyard, Cleber Oliveira, Maximilian Schiffer +2
We study optimal decision policies, represented as linear decision trees, for integer linear programs with a fixed feasible set and varying cost vectors. Once synthesized for a giv…
Breaking the Grid: Distance-Guided Reinforcement Learning in Large Discrete Action Spaces
Heiko Hoppe, Fabian Akkerman, Wouter van Heeswijk +1
Reinforcement Learning (RL) is increasingly applied to large-scale decision-making problems like logistics, scheduling, and recommender systems, but existing algorithms struggle wi…
Combinatorial Optimization Augmented Machine Learning
Maximilian Schiffer, Heiko Hoppe, Yue Su +2
Combinatorial optimization augmented machine learning (COAML) has recently emerged as a powerful paradigm for integrating predictive models with combinatorial decision-making. By e…