sMTL
Sparse Multi-Task Learning
Implements L0-constrained Multi-Task Learning and domain generalization algorithms. The algorithms are coded in Julia allowing for fast implementations of the coordinate descent and local combinatorial search algorithms. For more details, see a preprint of the paper: Loewinger et al., (2022) doi:10.48550/arXiv.2212.08697.
- Version0.1.0
- R versionunknown
- LicenseMIT
- LicenseLICENSE
- Needs compilation?No
- Last release02/06/2023
Team
Gabriel Loewinger
Rahul Mazumder
Show author detailsRolesAuthorKayhan Behdin
Show author detailsRolesAuthorGiovanni Parmigiani
Show author detailsRolesAuthorNational Science Foundation Grant DMS1810829
Show author detailsRolesfndNational Science Foundation Grant DMS2113707
Show author detailsRolesfndNational Science Foundation Grant NSF-IIS1718258
Show author detailsRolesfndOffice of Naval Research Grant ONR N000142112841
Show author detailsRolesfndNational Institute on Drug Abuse (NIH) Grant F31DA052153
Show author detailsRolesfnd
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- Imports5 packages
- Suggests2 packages