All regular talks are 15 minutes + 5 minutes Q&A.
09:00 - 09:10: Opening
09:10-10:30 Session 1
Formulations and Implementations, by Ali Irfan Mahmutogulları, Jayanta Mandi, Tias Guns
Simplicity Suffices for Parameter Noise Injection in Stochastic Gradient Descent, by Benjamin Leblanc, Louis-Jacob Lebel
Deep Reinforcement Learning Approach to Solving Clustered Vehicle Routing Problems, by Yue Yu, Yaoxin Wu
DROVER: Diffusion Routing with Verbal Reasoning, by Jesse van Remmerden, Zaharah Bukhsh, Yingqian Zhang
10:30-11:00 Coffee Break
11:00 - 11:45 Keynote 1: Understanding the Algorithmic Bias of Graph Neural Networks, by Christopher Morris (Aachen University, Germany)
11:45-12:45 Session 2:
Forge: Foundational Optimization Representations from Graph Embeddings, by Zohair Shafi, Serdar Kadioglu
Supervised Learning of Model Aware Variable Orderings in CP, by Georg Ringwelski, Julian Kirsch, Benedict Lelanz
Scheduling That Speaks: An Interpretable Programmatic Reinforcement Learning Framework, by Chengpeng Hu, Hendrik Baier, Yingqian Zhang
12:45 - 14:00 Lunch
14:00 - 14:45 Keynote 2: Combinatorial Optimization is Fundamental to Decision-Making across Science, by Wen Song (Shandong University, China)
14:45 - 15:25 Session 3:
Manifold Sampling via Entropy Maximization, by Cornelius V. Braun, Tilman Burghoff, Marc Toussaint
Prompt Segmentation and Annotation Optimisation: Controlling LLM Behaviour via Optimised Segment-Level Annotations, by Henry Xiao, Tong Li, Devika Prasad, Luke Gerschwitz, Anjin Liu, Coco Wu, Anna Leontjeva
15:25 - 16:00 Coffee Break
16:00 - 17:00 Session 4:
Scalable Decision-Focused Learning through Cost-Sensitive Regression, by Noah Schutte, Senne Berden, Tias Guns, Neil Yorke-Smith, Krzysztof Postek
Optimizing Emergency Blood Distribution: A Novel Multiplex Network Modeling Framework, by Suman Nandi, Giridhar Maji, Animesh Dutta
Learning-Guided State Partitioning for Decision Diagram Relaxations in Two-Stage Robust Optimization, by Michael Römer, Merve Bodur