Decentralized gradient methods: does topology matter?

Decentralized gradient methods: does topology matter?

28 February 2020

Giovanni Neglia

Papers citing "Decentralized gradient methods: does topology matter?"

12 / 12 papers shown

Title
Communication Optimization for Decentralized Learning atop Bandwidth-limited Edge Networks Tingyang Sun Tuan Nguyen Ting He 35 0 0 16 Apr 2025
Fully First-Order Methods for Decentralized Bilevel Optimization Xiaoyu Wang Xuxing Chen Shiqian Ma Tong Zhang 38 0 0 25 Oct 2024
Homogenizing Non-IID datasets via In-Distribution Knowledge Distillation for Decentralized Learning Deepak Ravikumar Gobinda Saha Sai Aparna Aketi Kaushik Roy 11 1 0 09 Apr 2023
Beyond spectral gap (extended): The role of the topology in decentralized learning Thijs Vogels Hadrien Hendrikx Martin Jaggi 24 3 0 05 Jan 2023
Straggler-Resilient Differentially-Private Decentralized Learning Yauhen Yakimenka Chung-Wei Weng Hsuan-Yin Lin E. Rosnes J. Kliewer 29 6 0 06 Dec 2022
Aggregation in the Mirror Space (AIMS): Fast, Accurate Distributed Machine Learning in Military Settings Ryan Yang Haizhou Du Andre Wibisono Patrick Baker 11 1 0 28 Oct 2022
Data-heterogeneity-aware Mixing for Decentralized Learning Yatin Dandi Anastasia Koloskova Martin Jaggi Sebastian U. Stich 33 18 0 13 Apr 2022
Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications Khaled B. Letaief Yuanming Shi Jianmin Lu Jianhua Lu 34 416 0 24 Nov 2021
Federated Multi-Task Learning under a Mixture of Distributions Othmane Marfoq Giovanni Neglia A. Bellet Laetitia Kameni Richard Vidal FedML 34 269 0 23 Aug 2021
Consensus Control for Decentralized Deep Learning Lingjing Kong Tao R. Lin Anastasia Koloskova Martin Jaggi Sebastian U. Stich 19 75 0 09 Feb 2021
Privacy Amplification by Decentralization Edwige Cyffers A. Bellet FedML 44 39 0 09 Dec 2020
Throughput-Optimal Topology Design for Cross-Silo Federated Learning Othmane Marfoq Chuan Xu Giovanni Neglia Richard Vidal FedML 67 85 0 23 Oct 2020