4 papers
OptiAgent: End-to-End Optimization Modeling via Multi-Agent Iterative Refinement
Adriana Laurindo Monteiro, Nayse Fagundes, Gabriel Mattos Langeloh +4
We propose OptiAgent, a multi-agent framework that, given a natural language description of an Operations Research problem, is able to output a solver-ready mathematical formulatio…
Nonparametric inference on Fokker-Plank and McKean-Vlasov models
Adriana Laurindo Monteiro, Roberto Imbuzeiro Oliveira
We propose a kernel-based estimator of the velocity field governing the transport and diffusion of -dimensional interacting particles. Assuming the initial positions are i.i.d.…
Evaluating Black-Box Vulnerabilities with Wasserstein-Constrained Data Perturbations
Adriana Laurindo Monteiro, Jean-Michel Loubes
The growing use of Machine Learning (ML) tools comes with critical challenges, such as limited model explainability. We propose a global explainability framework that leverages Opt…
Exposing the Illusion of Fairness: Auditing Vulnerabilities to Distributional Manipulation Attacks
Valentin Lafargue, Adriana Laurindo Monteiro, Emmanuelle Claeys +2
The rapid deployment of AI systems in high-stakes domains, including those classified as high-risk under the The EU AI Act (Regulation (EU) 2024/1689), has intensified the need for…