Union Support Recovery in Multi-Task Learning
Abstract
We sharply characterize the performance of different penalization schemes for the problem of selecting the relevant variables in the multi-task setting. Previous work focuses on the regression problem where conditions on the design matrix complicate the analysis. A clearer and simpler picture emerges by studying the Normal means model. This model, often used in the field of statistics, is a simplified model that provides a laboratory for studying complex procedures.
Cite
Text
Kolar et al. "Union Support Recovery in Multi-Task Learning." Journal of Machine Learning Research, 2011.Markdown
[Kolar et al. "Union Support Recovery in Multi-Task Learning." Journal of Machine Learning Research, 2011.](https://mlanthology.org/jmlr/2011/kolar2011jmlr-union/)BibTeX
@article{kolar2011jmlr-union,
title = {{Union Support Recovery in Multi-Task Learning}},
author = {Kolar, Mladen and Lafferty, John and Wasserman, Larry},
journal = {Journal of Machine Learning Research},
year = {2011},
pages = {2415-2435},
volume = {12},
url = {https://mlanthology.org/jmlr/2011/kolar2011jmlr-union/}
}