Carmina Fjellström

collaborators

2 papers

stat.ML2022

Deep learning, stochastic gradient descent and diffusion maps

Carmina Fjellström, Kaj Nyström

Stochastic gradient descent (SGD) is widely used in deep learning due to its computational efficiency, but a complete understanding of why SGD performs so well remains a major chal…

math.AP2022

Tug-of-war with Kolmogorov

Carmina Fjellström, Kaj Nyström, Matias Vestberg

We introduce a new class of strongly degenerate nonlinear parabolic PDEs $((p - 2) Δ_{\infty, X}^{N} + Δ_{X}) u (X, Y, t) + (m + p) (X \cdot \nabla_{Y} u (X, Y, t) - \partial_{t} u (X, Y, t)) = 0,$ $(X,Y,t)\in\mathb…