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cs.LG2026
Why SGD is not Brownian Motion: A New Perspective on Stochastic Dynamics
Igor Ignashin, Anna Radovskaya, Andrew Semenov +7
Stochastic Gradient Descent (SGD) is commonly modeled as a Langevin process, assuming that minibatch noise acts as Brownian motion. However, this approximation relies on a continuo…
cs.LG2025
Aligning Distributionally Robust Optimization with Practical Deep Learning Needs
Dmitrii Feoktistov, Igor Ignashin, Andrey Veprikov +4
While traditional Deep Learning (DL) optimization methods treat all training samples equally, Distributionally Robust Optimization (DRO) adaptively assigns importance weights to di…