2 papers
math.PR2026
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…
math.PR2024
A remarkable example on clustering of extremes for regularly-varying stochastic processes
Shuyang Bai, RafaÅ Kulik, Yizao Wang
The stable-regenerative multiple-stable model has been shown recently to have distinct candidate extremal index and extremal index. To understand further this rare phenomenon, two…