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cs.LG2024
Adaptive Methods through the Lens of SDEs: Theoretical Insights on the Role of Noise
Enea Monzio Compagnoni, Tianlin Liu, Rustem Islamov +3
Despite the vast empirical evidence supporting the efficacy of adaptive optimization methods in deep learning, their theoretical understanding is far from complete. This work intro…
cs.LG2024
SDEs for Minimax Optimization
Enea Monzio Compagnoni, Antonio Orvieto, Hans Kersting +2
Minimax optimization problems have attracted a lot of attention over the past few years, with applications ranging from economics to machine learning. While advanced optimization m…