Smart task orderings for active online multitask learning
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Authors
Pang, Paul
An, Jianbei
Zhao, Jing
Li, Xiaosong
Ban, Tao
Inoue, Daisuke
Sarrafzadeh, Hossein
An, Jianbei
Zhao, Jing
Li, Xiaosong
Ban, Tao
Inoue, Daisuke
Sarrafzadeh, Hossein
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Grantor
Date
2014-04-26
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Type
Conference Contribution - Paper in Published Proceedings
Ngā Upoko Tukutuku (Māori subject headings)
Keyword
oMTL (Online Multitask Learning with task selection)
task ordering
educational technology
task ordering
educational technology
ANZSRC Field of Research Code (2020)
Citation
Pang, S., An, J., Zhao, J., Li, X., Ban, T., Inoue, D., and Sarrafzadeh, A. (2014). Smart Task Orderings for Active Online Multitask Learning. . Proceedings of SIAM International Conference on Data Mining(Ed.), Philadelphia, Pennysylvania, USA.
Abstract
This paper promotes active oMTL (i.e., Online Multitask Learning with task selection) by proposing two smart task ordering approaches: QR-decomposition Ordering and Minimal-loss Ordering, in which the optimal sequence of tasks for oMTL is computed as the training data/tasks are being presented. Our experimental results on four real-world datasets show that the proposed task orderings outperform all existing task ordering approaches to active oMTL.
Publisher
Society for Industrial and Applied Mathematics, Activity Group on Data Mining and Analytics
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Society for Industrial and Applied Mathematics, Activity Group on Data Mining and Analytics
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