Publications

• MoMo: Momentum Models for Adaptive Learning Rates [abs] [pdf], Schaipp F, Ohana R, Eickenberg M, Defazio A, Gower R. ICML 2024.
• A Semismooth Newton Stochastic Proximal Point Algorithm with Variance Reduction [abs] [pdf], Milzarek A, Schaipp F, Ulbrich M. SIOPT 2024.
• SGD with Clipping is Secretly Estimating the Median Gradient [abs] [pdf], Schaipp F, Garrigos G, Simsekli U, Gower R. Arxiv preprint 2024.
• Robust gradient estimation in the presence of heavy-tailed noise [abs] [pdf], Schaipp F, Simsekli U, Gower R. NeurIPS Workshop Heavy Tails in Machine Learning 2023.
• A Stochastic Proximal Polyak Step Size [abs] [pdf], Schaipp F, Gower R, Ulbrich M. TMLR 2023.
• GGLasso - a Python package for General Graphical Lasso computation [abs] [pdf], Schaipp F, Vlasovets O, Müller C. JOSS 2022.