| A field guide to federated optimization J Wang, Z Charles, Z Xu, G Joshi, HB McMahan, M Al-Shedivat, G Andrew, ... arXiv preprint arXiv:2107.06917, 2021 | 380 | 2021 |
| FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout S Horvath, S Laskaridis, M Almeida, I Leontiadis, SI Venieris, ND Lane 35th Conference on Neural Information Processing Systems (NeurIPS 2021), 2021 | 271 | 2021 |
| Lower bounds and optimal algorithms for personalized federated learning F Hanzely, S Hanzely, S Horváth, P Richtárik 34th Conference on Neural Information Processing Systems (NeurIPS 2020), 2020 | 192 | 2020 |
| Stochastic Distributed Learning with Gradient Quantization and Variance Reduction S Horvath, D Kovalev, K Mishchenko, SU Stich, P Richtarik Optimization Methods and Software, DOI: 10.1080/10556788.2022.2117355, 2022 | 191* | 2022 |
| On Biased Compression for Distributed Learning A Beznosikov, S Horváth, P Richtárik, M Safaryan Journal of Machine Learning Research 24 (2023), 1--50, 2023 | 185 | 2023 |
| Optimal Client Sampling for Federated Learning W Chen, S Horvath, P Richtarik Published in Transactions on Machine Learning Research (TMLR), 2022 | 185 | 2022 |
| Don't Jump Through Hoops and Remove Those Loops: SVRG and Katyusha are Better Without the Outer Loop D Kovalev, S Horváth, P Richtárik ALT 2020 - Proceedings of the 31st International Conference on Algorithmic …, 2019 | 182 | 2019 |
| Natural compression for distributed deep learning S Horváth, CY Ho, L Horvath, AN Sahu, M Canini, P Richtárik 3rd Annual Conference on Mathematical and Scientific Machine Learning (MSML …, 2022 | 173 | 2022 |
| A Better Alternative to Error Feedback for Communication-Efficient Distributed Learning S Horváth, P Richtárik ICLR 2021 - International Conference on Learning Representations, 2020 | 66 | 2020 |
| Nonconvex variance reduced optimization with arbitrary sampling S Horváth, P Richtárik ICML 2019 - Proceedings of the 36th International Conference on Machine Learning, 2018 | 45 | 2018 |
| High-probability bounds for stochastic optimization and variational inequalities: the case of unbounded variance A Sadiev, M Danilova, E Gorbunov, S Horváth, G Gidel, P Dvurechensky, ... ICML 2023, 2023 | 43 | 2023 |
| Variance reduction is an antidote to byzantines: Better rates, weaker assumptions and communication compression as a cherry on the top E Gorbunov, S Horváth, P Richtárik, G Gidel ICLR 2023, 2022 | 43 | 2022 |
| Adaptivity of Stochastic Gradient Methods for Nonconvex Optimization S Horváth, L Lei, P Richtárik, MI Jordan SIAM Journal on Mathematics of Data Science (SIMODS), 2022 | 32 | 2022 |
| FLIX: A Simple and Communication-Efficient Alternative to Local Methods in Federated Learning E Gasanov, A Khaled, S Horváth, P Richtárik AISTATS 2022, International Conference on Artificial Intelligence and Statistics, 2021 | 31 | 2021 |
| Fedshuffle: Recipes for better use of local work in federated learning S Horváth, M Sanjabi, L Xiao, P Richtárik, M Rabbat Published in Transactions on Machine Learning Research (TMLR), 2022 | 28 | 2022 |
| Convergence of proximal point and extragradient-based methods beyond monotonicity: the case of negative comonotonicity E Gorbunov, A Taylor, S Horváth, G Gidel International Conference on Machine Learning, 11614-11641, 2023 | 25 | 2023 |
| Artificial intelligence-driven design of fuel mixtures N Kuzhagaliyeva, S Horváth, J Williams, A Nicolle, SM Sarathy Communications Chemistry 5 (1), 111, 2022 | 23 | 2022 |
| Fl_pytorch: optimization research simulator for federated learning K Burlachenko, S Horváth, P Richtárik Proceedings of the 2nd ACM International Workshop on Distributed Machine …, 2021 | 21 | 2021 |
| Hyperparameter transfer learning with adaptive complexity S Horváth, A Klein, P Richtárik, C Archambeau International conference on artificial intelligence and statistics, 1378-1386, 2021 | 18 | 2021 |
| Federated learning with regularized client participation G Malinovsky, S Horváth, K Burlachenko, P Richtárik Federated Learning and Analytics in Practice: Algorithms, Systems …, 2023 | 13 | 2023 |
Peter RichtarikProfessor, KAUSTEmail verificata su kaust.edu.sa
