Package: sMTL
Title: Sparse Multi-Task Learning
Version: 0.1.0
Authors@R: c(person("Gabriel", "Loewinger", email = "gloewinger@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-0755-8520")), 
		person("Kayhan", "Behdin", email = "behdink@mit.edu", role = c("aut")),
		person("Giovanni", "Parmigiani", email = "gp@jimmy.harvard.edu", role = c("aut")), 
		person("Rahul", "Mazumder", email = "rahulmaz@mit.edu", role = c("aut")),
		person("National Science Foundation", "Grant DMS1810829", role = c("fnd")),
		person("National Science Foundation", "Grant DMS2113707", role = c("fnd")),
		person("National Science Foundation", "Grant NSF-IIS1718258,", role = c("fnd")),
		person("Office of Naval Research", "Grant ONR N000142112841", role = c("fnd")),
		person("National Institute on Drug Abuse (NIH)", "Grant F31DA052153", role = c("fnd")))
Description: 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) <arXiv:2212.08697>.
URL: https://github.com/gloewing/sMTL,
        https://rpubs.com/gloewinger/996629
BugReports: https://github.com/gloewing/sMTL/issues
Maintainer: Gabriel Loewinger <gloewinger@gmail.com>
Depends: R (>= 3.5.0)
License: MIT + file LICENSE
Encoding: UTF-8
Imports: glmnet, JuliaCall, JuliaConnectoR, caret, dplyr
RoxygenNote: 7.2.1
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2023-02-04 22:58:56 UTC; loewingergc
Author: Gabriel Loewinger [aut, cre] (<https://orcid.org/0000-0002-0755-8520>),
  Kayhan Behdin [aut],
  Giovanni Parmigiani [aut],
  Rahul Mazumder [aut],
  National Science Foundation Grant DMS1810829 [fnd],
  National Science Foundation Grant DMS2113707 [fnd],
  National Science Foundation Grant NSF-IIS1718258, [fnd],
  Office of Naval Research Grant ONR N000142112841 [fnd],
  National Institute on Drug Abuse (NIH) Grant F31DA052153 [fnd]
Repository: CRAN
Date/Publication: 2023-02-06 11:20:02 UTC
Built: R 4.6.0; ; 2026-04-25 13:52:25 UTC; unix
