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cs.LG2026
Everywhere Learning: Artificial Intelligence with Pointwise Constraints
Ignacio Boero, Ignacio Hounie, Luiz Chamon +1
Everywhere learning is a new paradigm whereby Artificial Intelligence (AI) systems are trained to satisfy loss constraints with probability one over the data distribution. This is…
cs.LG2025
AL-CoLe: Augmented Lagrangian for Constrained Learning
Ignacio Boero, Ignacio Hounie, Alejandro Ribeiro
Despite the non-convexity of most modern machine learning parameterizations, Lagrangian duality has become a popular tool for addressing constrained learning problems. We revisit A…
cs.LG2025
Learning to Optimally Dispatch Power: Performance on a Nation-Wide Real-World Dataset
Ignacio Boero, Santiago Diaz, Tomás Vázquez +3
The Optimal Reactive Power Dispatch (ORPD) problem plays a crucial role in power system operations, ensuring voltage stability and minimizing power losses. Recent advances in machi…