Multi-task learning: Difference between revisions

Revision as of 20:24, 7 December 2020

Revision as of 20:27, 7 December 2020

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* Clustered Multi-Task Learning<ref>Jacob, L., Bach, F., & Vert, J. (2008). [https://hal-ensmp.archives-ouvertes.fr/docs/00/32/05/73/PDF/cmultitask.pdf Clustered multi-task learning: A convex formulation]. Advances in Neural Information Processing Systems， 2008</ref><ref>Zhou, J., Chen, J., & Ye, J. (2011). [http://papers.nips.cc/paper/4292-clustered-multi-task-learning-via-alternating-structure-optimization.pdf Clustered multi-task learning via alternating structure optimization]. Advances in Neural Information Processing Systems.</ref>

* Multi-Task Learning with Graph Structures

The Correlated-Multi-Task learning R package <ref>{{Cite journal|last=Gao|first=Xin|last2=Zhong|first2=Yuan|date=2019-03-27|title=FusionLearn: a biomarker selection algorithm on cross-platform data|url=http://dx.doi.org/10.1093/bioinformatics/btz223|journal=Bioinformatics|volume=35|issue=21|pages=4465–4468|doi=10.1093/bioinformatics/btz223|issn=1367-4803}}</ref> <ref>{{Citation|last=Gao|first=Xin|title=FusionLearn: Fusion Learning|date=2019-03-09|url=https://cran.r-project.org/package=FusionLearn|access-date=2020-12-07|last2=Zhong|first2=Yuan|last3=Carroll|first3=and Raymond J.}}</ref>inplementsimplements the following procedures:

* Pseudo-likelihood based estimation