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Found 5 papers, 4 papers with code
From Large Language Models and Optimization to Decision Optimization CoPilot: A Research Manifesto
Significantly simplifying the creation of optimization models for real-world business problems has long been a major goal in applying mathematical optimization more widely to important business and societal decisions.
Finding Regions of Counterfactual Explanations via Robust Optimization
To this end, our method provides a whole region of CEs allowing the user to choose a suitable recourse to obtain a desired outcome.
Robust Upper Bounds for Adversarial Training
We introduce a new approach to adversarial training by minimizing an upper bound of the adversarial loss that is based on a holistic expansion of the network instead of separate bounds for each layer.
Mixed-Integer Optimization with Constraint Learning
The case studies illustrate the framework's ability to generate high-quality prescriptions as well as the value added by the trust region, the use of ensembles to control model robustness, the consideration of multiple machine learning methods, and the inclusion of multiple learned constraints.
Optimization with Constraint Learning: A Framework and Survey
Many real-life optimization problems frequently contain one or more constraints or objectives for which there are no explicit formulas.
