An Improved Analysis of Gradient Tracking for Decentralized Machine Learning

von Koloskova, Anastasiia
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 14 of 36 (2022)

Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning

von Koloskova, Anastasiia
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 23 of 50 (2023)

Ensemble Distillation for Robust Model Fusion in Federated Learning

von Lin, Tao
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 3 of 27 (2021)

EXTRAPOLATION FOR LARGE-BATCH TRAINING IN DEEP LEARNING

von Lin, Tao
Veröffentlicht in International Conference on Machine Learning (37. : 2020 : Online) 37th International Conference on Machine Learning (ICML 2020) ; Part 8 of 15 (2021)

QUASI-GLOBAL MOMENTUM: ACCELERATING DECENTRALIZED DEEP LEARNING ON HETEROGENEOUS DATA

von LIN, TAO
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 9 of 16 (2022)

A UNIFIED THEORY OF DECENTRALIZED SGD WITH CHANGING TOPOLOGY AND LOCAL UPDATES

von Koloskova, Anastasia
Veröffentlicht in International Conference on Machine Learning (37. : 2020 : Online) 37th International Conference on Machine Learning (ICML 2020) ; Part 7 of 15 (2021)

CONSENSUS CONTROL FOR DECENTRALIZED DEEP LEARNING

von KONG, LINGJING
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 8 of 16 (2022)

Decentralized Local Stochastic Extra-Gradient for Variational Inequalities

von Beznosikov, Aleksandr
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 49 of 50 (2023)

RelaySum for Decentralized Deep Learning on Heterogeneous Data

von Vogels, Thijs
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 33 of 36 (2022)

Breaking the centralized barrier for cross-device federated learning

von Karimireddy, Sai Praneeth
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 34 of 36 (2022)