Portrait de Lucas Maes

Lucas Maes

lucas.maes@mila.quebec
Doctorat - UdeM
Co-supervisor
Simon Lacoste-Julien
Sujets de recherche
Apprentissage de représentations
Optimisation
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GitHub

Publications

Understanding Adam Requires Better Rotation Dependent Assumptions
Tianyue H. Zhang
Lucas Maes
Alan Milligan
Alexia Jolicoeur-Martineau
Ioannis Mitliagkas
Damien Scieur
Simon Lacoste-Julien
Charles Guille-escuret
Despite its widespread adoption, Adam's advantage over Stochastic Gradient Descent (SGD) lacks a comprehensive theoretical explanation. This… (voir plus) paper investigates Adam's sensitivity to rotations of the parameter space. We observe that Adam's performance in training transformers degrades under random rotations of the parameter space, indicating a crucial sensitivity to the choice of basis in practice. This reveals that conventional rotation-invariant assumptions are insufficient to capture Adam's advantages theoretically. To better understand the rotation-dependent properties that benefit Adam, we also identify structured rotations that preserve or even enhance its empirical performance. We then examine the rotation-dependent assumptions in the literature and find that they fall short in explaining Adam's behaviour across various rotation types. In contrast, we verify the orthogonality of the update as a promising indicator of Adam's basis sensitivity, suggesting it may be the key quantity for developing rotation-dependent theoretical frameworks that better explain its empirical success.
2025-12-02
Neural Information Processing Systems (Accept (poster))
doi.org
openreview.net