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Filip Hanzely
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2020 – today
- 2023
- [j4]Filip Hanzely, Boxin Zhao, Mladen Kolar:
Personalized Federated Learning: A Unified Framework and Universal Optimization Techniques. Trans. Mach. Learn. Res. 2023 (2023) - 2022
- [i19]Boxiang Lyu, Filip Hanzely, Mladen Kolar:
Personalized Federated Learning with Multiple Known Clusters. CoRR abs/2204.13619 (2022) - 2021
- [j3]Filip Hanzely
, Peter Richtárik
, Lin Xiao
:
Accelerated Bregman proximal gradient methods for relatively smooth convex optimization. Comput. Optim. Appl. 79(2): 405-440 (2021) - [j2]Filip Hanzely
, Peter Richtárik
:
Fastest rates for stochastic mirror descent methods. Comput. Optim. Appl. 79(3): 717-766 (2021) - [c11]Eduard Gorbunov, Filip Hanzely, Peter Richtárik:
Local SGD: Unified Theory and New Efficient Methods. AISTATS 2021: 3556-3564 - [c10]Mher Safaryan, Filip Hanzely, Peter Richtárik:
Smoothness Matrices Beat Smoothness Constants: Better Communication Compression Techniques for Distributed Optimization. NeurIPS 2021: 25688-25702 - [i18]Mher Safaryan
, Filip Hanzely, Peter Richtárik
:
Smoothness Matrices Beat Smoothness Constants: Better Communication Compression Techniques for Distributed Optimization. CoRR abs/2102.07245 (2021) - [i17]Filip Hanzely, Boxin Zhao, Mladen Kolar:
Personalized Federated Learning: A Unified Framework and Universal Optimization Techniques. CoRR abs/2102.09743 (2021) - [i16]Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Agüera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas N. Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horváth
, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecný, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtárik
, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake E. Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu:
A Field Guide to Federated Optimization. CoRR abs/2107.06917 (2021) - 2020
- [b1]Filip Hanzely
:
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters. King Abdullah University of Science and Technology, Thuwal, Saudi Arabia, 2020 - [j1]Aritra Dutta
, Filip Hanzely
, Jingwei Liang
, Peter Richtárik
:
Best Pair Formulation & Accelerated Scheme for Non-Convex Principal Component Pursuit. IEEE Trans. Signal Process. 68: 6128-6141 (2020) - [c9]Eduard Gorbunov, Filip Hanzely, Peter Richtárik:
A Unified Theory of SGD: Variance Reduction, Sampling, Quantization and Coordinate Descent. AISTATS 2020: 680-690 - [c8]Filip Hanzely, Nikita Doikov, Yurii E. Nesterov, Peter Richtárik:
Stochastic Subspace Cubic Newton Method. ICML 2020: 4027-4038 - [c7]Filip Hanzely, Dmitry Kovalev, Peter Richtárik:
Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems. ICML 2020: 4039-4048 - [c6]Filip Hanzely, Slavomír Hanzely, Samuel Horváth, Peter Richtárik:
Lower Bounds and Optimal Algorithms for Personalized Federated Learning. NeurIPS 2020 - [c5]Konstantin Mishchenko, Filip Hanzely, Peter Richtárik:
99% of Worker-Master Communication in Distributed Optimization Is Not Needed. UAI 2020: 979-988 - [i15]Filip Hanzely, Dmitry Kovalev, Peter Richtárik
:
Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems. CoRR abs/2002.04670 (2020) - [i14]Filip Hanzely, Peter Richtárik
:
Federated Learning of a Mixture of Global and Local Models. CoRR abs/2002.05516 (2020) - [i13]Filip Hanzely
, Nikita Doikov, Peter Richtárik
, Yurii E. Nesterov:
Stochastic Subspace Cubic Newton Method. CoRR abs/2002.09526 (2020) - [i12]Filip Hanzely
:
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters. CoRR abs/2008.11824 (2020) - [i11]Filip Hanzely
, Slavomír Hanzely, Samuel Horváth
, Peter Richtárik
:
Lower Bounds and Optimal Algorithms for Personalized Federated Learning. CoRR abs/2010.02372 (2020) - [i10]Eduard Gorbunov, Filip Hanzely
, Peter Richtárik
:
Local SGD: Unified Theory and New Efficient Methods. CoRR abs/2011.02828 (2020)
2010 – 2019
- 2019
- [c4]Aritra Dutta, Filip Hanzely
, Peter Richtárik
:
A Nonconvex Projection Method for Robust PCA. AAAI 2019: 1468-1476 - [c3]Filip Hanzely, Peter Richtárik:
Accelerated Coordinate Descent with Arbitrary Sampling and Best Rates for Minibatches. AISTATS 2019: 304-312 - [i9]Filip Hanzely
, Jakub Konecný, Nicolas Loizou, Peter Richtárik
, Dmitry Grishchenko:
A Privacy Preserving Randomized Gossip Algorithm via Controlled Noise Insertion. CoRR abs/1901.09367 (2019) - [i8]Konstantin Mishchenko
, Filip Hanzely
, Peter Richtárik
:
99% of Parallel Optimization is Inevitably a Waste of Time. CoRR abs/1901.09437 (2019) - [i7]Aritra Dutta, Filip Hanzely
, Jingwei Liang, Peter Richtárik
:
Best Pair Formulation & Accelerated Scheme for Non-convex Principal Component Pursuit. CoRR abs/1905.10598 (2019) - [i6]Eduard Gorbunov
, Filip Hanzely
, Peter Richtárik
:
A Unified Theory of SGD: Variance Reduction, Sampling, Quantization and Coordinate Descent. CoRR abs/1905.11261 (2019) - [i5]Filip Hanzely
, Peter Richtárik
:
One Method to Rule Them All: Variance Reduction for Data, Parameters and Many New Methods. CoRR abs/1905.11266 (2019) - 2018
- [c2]Robert M. Gower, Filip Hanzely, Peter Richtárik, Sebastian U. Stich:
Accelerated Stochastic Matrix Inversion: General Theory and Speeding up BFGS Rules for Faster Second-Order Optimization. NeurIPS 2018: 1626-1636 - [c1]Filip Hanzely, Konstantin Mishchenko, Peter Richtárik:
SEGA: Variance Reduction via Gradient Sketching. NeurIPS 2018: 2086-2097 - [i4]Robert M. Gower, Filip Hanzely
, Peter Richtárik
, Sebastian U. Stich:
Accelerated Stochastic Matrix Inversion: General Theory and Speeding up BFGS Rules for Faster Second-Order Optimization. CoRR abs/1802.04079 (2018) - [i3]Filip Hanzely
, Peter Richtárik
:
Fastest Rates for Stochastic Mirror Descent Methods. CoRR abs/1803.07374 (2018) - [i2]Aritra Dutta, Filip Hanzely
, Peter Richtárik
:
A Nonconvex Projection Method for Robust PCA. CoRR abs/1805.07962 (2018) - [i1]Filip Hanzely
, Konstantin Mishchenko
, Peter Richtárik
:
SEGA: Variance Reduction via Gradient Sketching. CoRR abs/1809.03054 (2018)
Coauthor Index
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last updated on 2024-08-02 20:22 CEST by the dblp team
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