Web: http://arxiv.org/abs/2111.04798

May 9, 2022, 1:11 a.m. | Wasu Piriyakulkij, Cristina Menghini, Ross Briden, Nihal V. Nayak, Jeffrey Zhu, Elaheh Raisi, Stephen H. Bach

cs.LG updates on arXiv.org arxiv.org

Machine learning practitioners often have access to a spectrum of data:
labeled data for the target task (which is often limited), unlabeled data, and
auxiliary data, the many available labeled datasets for other tasks. We
describe TAGLETS, a system built to study techniques for automatically
exploiting all three types of data and creating high-quality, servable
classifiers. The key components of TAGLETS are: (1) auxiliary data organized
according to a knowledge graph, (2) modules encapsulating different methods for
exploiting auxiliary and …

arxiv data learning semi-supervised semi-supervised learning supervised learning

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