PySCIPOpt-ML: Embedding Trained Machine Learning Models into Mixed-Integer Programs

2025/01/01 by Mark Turner, Antonia Chmiela, Thorsten Koch +1 · 1 voice
Computer Science · #Adversarial Robustness in Machine Learning #Machine Learning and Algorithms #Machine Learning and Data Classification

paper · doi:10.1007/978-3-031-95976-9_14

crossref issued 2025/01/01 · crossref published 2025/01/01 · crossref published-print 2025/01/01 · openalex publication_date 2025/01/01 · crossref created 2025/06/28 · crossref published-online 2025/06/29 · openalex created_date 2025/10/10 · crossref deposited 2026/04/30 · crossref indexed 2026/07/14 · openalex updated_date 2026/07/29

Citations

• Pyomo — Optimization Modeling in Python
• Gradient-based learning applied to document recognition
• Strong mixed-integer programming formulations for trained neural networks
• PyTorch: An Imperative Style, High-Performance Deep Learning Library

Discussions

• We continue with Mark Turner's talk on the PySCIPOpt-ML framekwork, which allows you to embed trained machine learning models into mixed-integer programs. doi.org/10.1007/978-... [bsky, 3 points, 1 comments]