{ "_id": "6ada6af8dd3792e77323894e", "Package": "orthoMTL", "Type": "Package", "Title": "Multi-Task Learning with Orthogonal Constraints", "Version": "0.1.1", "Authors@R": "c(\nperson(\"Kevin\", \"Vervier\",\nemail = \"kevin.vervier@novartis.com\",\nrole = c(\"aut\", \"cre\")),\nperson(\"Novartis Pharma AG\", role = c(\"cph\", \"fnd\")))", "Description": "Fits regularised multi-task learning models where\nrelationships between tasks are controlled via orthogonality or\ndisjoint-support constraints. Supports regression, binary\nclassification, and censored survival data. In survival mode,\ntime-to-event outcomes are converted into binary labels at\nuser-defined thresholds, enabling the discovery of features\nwith time-varying effects that standard proportional-hazards\nmodels cannot detect. Implements the penalty described in\nVervier et al. 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