| MoMo: Momentum Models for Adaptive Learning Rates F Schaipp, R Ohana, M Eickenberg, A Defazio, RM Gower International Conference on Machine Learning 41, 43542-43570, 2024 | 16 | 2024 |
| A Stochastic Proximal Polyak Step Size F Schaipp, RM Gower, M Ulbrich Transactions on Machine Learning Research, 2023 | 16 | 2023 |
| The Surprising Agreement Between Convex Optimization Theory and Learning-Rate Scheduling for Large Model Training F Schaipp, A Hägele, A Taylor, U Simsekli, F Bach International Conference on Machine Learning 267, 53267--53294, 2025 | 15 | 2025 |
| GGLasso--a Python package for General Graphical Lasso computation F Schaipp, CL Müller, O Vlasovets Journal of Open Source Software 6 (68), 3865, 2021 | 15 | 2021 |
| A semismooth Newton stochastic proximal point algorithm with variance reduction A Milzarek, F Schaipp, M Ulbrich SIAM Journal on Optimization 34 (1), 1157-1185, 2024 | 14 | 2024 |
| Function Value Learning: Adaptive Learning Rates Based on the Polyak Stepsize and Function Splitting in ERM G Garrigos, RM Gower, F Schaipp arXiv preprint arXiv:2307.14528, 2023 | 5 | 2023 |
| Analysis of an Idealized Stochastic Polyak Method and its Application to Black-Box Model Distillation RM Gower, G Garrigos, N Loizou, D Oikonomou, K Mishchenko, ... arXiv preprint arXiv:2504.01898, 2025 | 4 | 2025 |
| Decay No More F Schaipp The Second Blogpost Track at ICLR 2023, 2023 | 3 | 2023 |
| Tracking the Median of Gradients with a Stochastic Proximal Point Method F Schaipp, G Garrigos, U Simsekli, R Gower Transactions on Machine Learning Research, 2025 | 2* | 2025 |
| Optimization Benchmark for Diffusion Models on Dynamical Systems F Schaipp arXiv preprint arXiv:2510.19376, 2025 | 1 | 2025 |
| How to jointly tune learning rate and weight decay for AdamW F Schaipp Blog post, 2024 | 1 | 2024 |
| Robust gradient estimation in the presence of heavy-tailed noise F Schaipp, U Simsekli, RM Gower NeurIPS 2023 Workshop Heavy Tails in Machine Learning, 2023 | 1 | 2023 |
| Topics in Stochastic Optimization: Learning with Implicit and Adaptive Steps F Schaipp Technische Universität München, 2024 | | 2024 |
Robert Mansel GowerResearch Scientist, Center for Computational Mathematics, Flatiron Institute, Simons FoundationVerified email at flatironinstitute.org
