3 accepted papers
Strategic classification studies the interaction between decision models and agents who strategically manipulate their features for favorable outcomes. Existing SC frameworks typically rely on the idealized assumption that agents are strictly rational. However, evidence from behavioral economics and…
Tabular foundation models via pretrained prior-data fitted networks (PFNs) achieve remarkable generalization performance on arbitrary testing tabular data, when sample distributions are independent of the deployed classifiers, i.e., a non-strategic regime. In a variety of real-world scenarios, howev…
Strategic classification (SC) explores how individuals or entities modify their features strategically to achieve favorable classification outcomes. However, existing SC methods, which are largely based on linear models or shallow neural networks, face significant limitations in terms of scalability…