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math.OC2025
Inexact subgradient methods for semialgebraic functions
Jérôme Bolte, Tam Le, Ãric Moulines +1
Motivated by the extensive application of approximate gradients in machine learning and optimization, we investigate inexact subgradient methods subject to persistent additive erro…
math.OC2025
Universal generalization guarantees for Wasserstein distributionally robust models
Tam Le, Jérôme Malick
Distributionally robust optimization has emerged as an attractive way to train robust machine learning models, capturing data uncertainty and distribution shifts. Recent statistica…