Sebastian Urban Stich
École Polytechnique Fédérale de Lausanne
H-index: 31
Europe-Switzerland
Top articles of Sebastian Urban Stich
Title | Journal | Author(s) | Publication Date |
|---|---|---|---|
Federated Optimization with Doubly Regularized Drift Correction | arXiv preprint arXiv:2404.08447 | Xiaowen Jiang Anton Rodomanov Sebastian U Stich | 2024/4/12 |
Decentralized gradient tracking with local steps | Optimization Methods and Software | Yue Liu Tao Lin Anastasia Koloskova Sebastian U Stich | 2024/3/12 |
Non-Convex Stochastic Composite Optimization with Polyak Momentum | arXiv preprint arXiv:2403.02967 | Yuan Gao Anton Rodomanov Sebastian U Stich | 2024/3/5 |
EControl: Fast Distributed Optimization with Compression and Error Control | Yuan Gao Rustem Islamov Sebastian Stich | 2024/5/7 | |
Spectral Preconditioning for Gradient Methods on Graded Non-convex Functions | arXiv preprint arXiv:2402.04843 | Nikita Doikov Sebastian U Stich Martin Jaggi | 2024/2/7 |
Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates | arXiv preprint arXiv:2306.05100 | Siqi Zhang Sayantan Choudhury Sebastian U Stich Nicolas Loizou | 2023/6/8 |
An improved analysis of per-sample and per-update clipping in federated learning | Bo Li Xiaowen Jiang Mikkel N Schmidt Tommy Sonne Alstrøm Sebastian U Stich | 2023/10/13 | |
Synthetic data shuffling accelerates the convergence of federated learning under data heterogeneity | arXiv preprint arXiv:2306.13263 | Bo Li Yasin Esfandiari Mikkel N Schmidt Tommy S Alstrøm Sebastian U Stich | 2023/6/23 |
On the Convergence of Local SGD Under Third-Order Smoothness and Hessian Similarity | Ali Zindari Ruichen Luo Sebastian U Stich | 2023/12/13 | |
Stochastic distributed learning with gradient quantization and double-variance reduction | Optimization Methods and Software | Samuel Horváth Dmitry Kovalev Konstantin Mishchenko Peter Richtárik Sebastian Stich | 2023/1/2 |
Adaptive SGD with Polyak stepsize and Line-search: Robust Convergence and Variance Reduction | Xiaowen Jiang Sebastian U Stich | 2023/12/11 | |
On the effectiveness of partial variance reduction in federated learning with heterogeneous data | Bo Li Mikkel N Schmidt Tommy S Alstrøm Sebastian U Stich | 2023 | |
Special Properties of Gradient Descent with Large Learning Rates | Amirkeivan Mohtashami Martin Jaggi Sebastian Stich | 2023 | |
Revisiting Gradient Clipping: Stochastic bias and tight convergence guarantees | ICML 2023 | Anastasia Koloskova* Hadrien Hendrikx* Sebastian U Stich | 2023/5/2 |
Noise Injection Irons Out Local Minima and Saddle Points | Konstantin Mishchenko Sebastian U Stich | 2023/12/13 | |
Locally Adaptive Federated Learning via Stochastic Polyak Stepsizes | arXiv preprint arXiv:2307.06306 | Sohom Mukherjee Nicolas Loizou Sebastian U Stich | 2023/7/12 |
Diversity-adjusted adaptive step size | Parham Yazdkhasti Xiaowen Jiang Sebastian U Stich | 2023/12/13 | |
Tackling benign nonconvexity with smoothing and stochastic gradients | arXiv preprint arXiv:2202.09052 | Harsh Vardhan Sebastian U Stich | 2022/2/18 |
Decentralized Local Stochastic Extra-Gradient for Variational Inequalities | Aleksandr Beznosikov Pavel Dvurechensky Anastasia Koloskova Valentin Samokhin Sebastian U Stich | 2022/11/28 | |
Characterizing & Finding Good Data Orderings for Fast Convergence of Sequential Gradient Methods | arXiv preprint arXiv:2202.01838 | Amirkeivan Mohtashami Sebastian Stich Martin Jaggi | 2022/2/3 |
Co-Authors
