Convergence of Stochastic Gradient Descent with mini-batching and infinite variance

Bartosz Glowacki, Rafal Kulik, Philippe Soulier

Stochastic gradient descent (SGD) with mini-batching is a standard tool in large-scale optimization, yet its theoretical properties under heavy-tailed gradient noise remain largely…