Many-Task Federated Learning: A New Problem Setting and A Simple Baseline

Author:

Cai Ruisi1,Chen Xiaohan2,Liu Shiwei1,Srinivasa Jayanth3,Lee Myungjin3,Kompella Ramana3,Wang Zhangyang1

Affiliation:

1. University of Texas at Austin

2. Alibaba US

3. Cisco Systems

Publisher

IEEE

Reference28 articles.

1. Federated multi-task learning under a mixture of distributions;marfoq;Advances in neural information processing systems,2021

2. M3vit: Mixture-of-experts vision transformer for efficient multi-task learning with model-accelerator co-design;liang;Advances in neural information processing systems,2022

3. Cross-Stitch Networks for Multi-task Learning

4. Communicationefficient learning of deep networks from decentralized data;mcmahan;Artificial Intelligence and Statistics,2017

5. Federated optimization in heterogeneous networks;li;Proceedings of Machine Learning and Systems,2020

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Federated Multi-Task Learning on Non-IID Data Silos: An Experimental Study;Proceedings of the 2024 International Conference on Multimedia Retrieval;2024-05-30

2. Personalized Federated Learning via Backbone Self-Distillation;ACM Multimedia Asia 2023;2023-12-06

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