FedWM: Federated Crowdsourcing Workforce Management Service for Productive Laziness-Reference-Cited by-同舟云学术

FedWM: Federated Crowdsourcing Workforce Management Service for Productive Laziness

Published:2023-07 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Web Services (ICWS)
language:
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Author:

Shi Zhuan¹,Yao Zhenyu²,Yi Liping³,Yu Han⁴,Zhang Lan¹,Li Xiang-Yang¹

Affiliation:

1. University of Science and Technology of China,School of Computer Science and Technology,China

2. Univerisity of Liverpool,Department of Mathematical Sciences,United Kingdom

3. Nankai University,College of Computer Science,China

4. Nanyang Technological University,School of Computer Science and Engineering,Singapore

Funder

Fundamental Research Funds for the Central Universities

National Research Foundation Singapore

Nanyang Technological University

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10248204/10248227/10248239.pdf?arnumber=10248239

Reference38 articles.

1. GTG-Shapley: Efficient and Accurate Participant Contribution Evaluation in Federated Learning

2. Algorithmic Management for Improving Collective Productivity in Crowdsourcing

3. Communication-efficient learning of deep networks from decentralized data;mcmahan;Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS'17),2017

4. Mitigating Herding in Hierarchical Crowdsourcing Networks

5. Gradient-based learning applied to document recognition

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