Distributed multi-task classification: a decentralized online learning approach
By Chi Zhang, Peilin Zhao, Shuji Hao, Y. C. Soh, Bu-Sung Lee, Chunyan Miao, Steven C. H. Hoi. 2017
30 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computational Mechanics, Computer Networks and Communications
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In Artificial Intelligence
In Computational Mechanics
In Computer Networks and Communications
Citations in the corpus
- Decentralized Online Learning: Take Benefits from Others’ Data without Sharing Your Own to Track Global Trend (2019, neutral): “Additionally, many decentralized online optimization methods are proposed, for example, decentralized online multi-task learning [42], decentralized online ADMM [36], decentralized online gradient descent [2], decentralized continuous-time online saddle-point method [24], decentralized online Nester”
- Asynchronous Decentralized Online Learning (2021, background): “Many different algorithms have been proposed [31, 32, 22, 15, 28, 16, 24] and successfully applied in various application scenarios, such as recommendation systems [29], energy management [5] and cooperative navigation [21].”
- Graph Representation Learning in Biomedicine and Healthcare (2021, unknown): “Feature engineering—the process of extracting predetermined features from a network to suit a user-specified machine-learning method 54 —is also a common approach applied to machine learning on networks.”