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2020 – today
- 2024
[c9]Ali Beikmohammadi
, Sarit Khirirat, Sindri Magnússon:
Compressed Federated Reinforcement Learning with a Generative Model. ECML/PKDD (4) 2024: 20-37- [i6]Ali Beikmohammadi, Sarit Khirirat, Sindri Magnússon:
Distributed Momentum Methods Under Biased Gradient Estimations. CoRR abs/2403.00853 (2024) - [i5]Ali Beikmohammadi, Sarit Khirirat, Sindri Magnússon:
On the Convergence of Federated Learning Algorithms without Data Similarity. CoRR abs/2403.02347 (2024) - [i4]Ali Beikmohammadi, Sarit Khirirat, Sindri Magnússon:
Compressed Federated Reinforcement Learning with a Generative Model. CoRR abs/2404.10635 (2024) - 2023
- [j2]Sarit Khirirat, Xiaoyu Wang, Sindri Magnússon, Mikael Johansson:
Improved Step-Size Schedules for Proximal Noisy Gradient Methods. IEEE Trans. Signal Process. 71: 189-201 (2023) - [i3]Xiangjian Hou, Sarit Khirirat, Mohammad Yaqub, Samuel Horváth:
Improving Performance of Private Federated Models in Medical Image Analysis. CoRR abs/2304.05127 (2023) - [i2]Sarit Khirirat, Eduard Gorbunov, Samuel Horváth, Rustem Islamov, Fakhri Karray, Peter Richtárik:
Clip21: Error Feedback for Gradient Clipping. CoRR abs/2305.18929 (2023) - 2022
- [b1]Sarit Khirirat:
First-Order Algorithms for Communication Efficient Distributed Learning. Royal Institute of Technology, Stockholm, Sweden, 2022 - [c8]Sarit Khirirat, Sindri Magnússon, Mikael Johansson:
Eco-Fedsplit: Federated Learning with Error-Compensated Compression. ICASSP 2022: 5952-5956 - [c7]Erik Berglund, Sarit Khirirat, Xiaoyu Wang:
Zeroth-Order Randomized Subspace Newton Methods. ICASSP 2022: 6002-6006 - 2021
- [j1]Sarit Khirirat, Sindri Magnússon, Mikael Johansson:
Compressed Gradient Methods With Hessian-Aided Error Compensation. IEEE Trans. Signal Process. 69: 998-1011 (2021) - [c6]Sarit Khirirat, Sindri Magnússon, Arda Aytekin, Mikael Johansson:
A Flexible Framework for Communication-Efficient Machine Learning. AAAI 2021: 8101-8109 - [c5]Sarit Khirirat, Xiaoyu Wang, Sindri Magnússon, Mikael Johansson:
Improved Step-Size Schedules for Noisy Gradient Methods. ICASSP 2021: 3655-3659
2010 – 2019
- 2019
- [c4]Sarit Khirirat, Sindri Magnússon, Mikael Johansson:
Convergence Bounds for Compressed Gradient Methods with Memory Based Error Compensation. ICASSP 2019: 2857-2861 - 2018
- [c3]Sarit Khirirat, Mikael Johansson, Dan Alistarh:
Gradient compression for communication-limited convex optimization. CDC 2018: 166-171 - [c2]Dan Alistarh, Torsten Hoefler, Mikael Johansson, Nikola Konstantinov, Sarit Khirirat, Cédric Renggli:
The Convergence of Sparsified Gradient Methods. NeurIPS 2018: 5977-5987 - [i1]Dan Alistarh, Torsten Hoefler, Mikael Johansson, Sarit Khirirat, Nikola Konstantinov, Cédric Renggli:
The Convergence of Sparsified Gradient Methods. CoRR abs/1809.10505 (2018) - 2017
- [c1]Sarit Khirirat, Hamid Reza Feyzmahdavian, Mikael Johansson:
Mini-batch gradient descent: Faster convergence under data sparsity. CDC 2017: 2880-2887
Coauthor Index
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last updated on 2024-09-10 02:12 CEST by the dblp team
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