This paper describes Snorkel, a system that enables users to help shape, create, and manage training data for Software 2.0 stacks.
Presenting Snorkel MeTal, an end-to-end system for multi-task learning.
Introducing Fonduer, a machine-learning-based KBC system for richly formatted data.
This paper showcases methods for unsupervised mining of fashion attributes from Instagram text, which can enable a new kind of user recommendation in the fashion domain.
Introducing Snorkel, a new system for quickly creating, managing, and modeling training datasets.
Automating data augmentation by learning a generative sequence model over user-specified transformation functions.
Proposing a structure estimation method that is 100x faster than a maximum likelihood approach for training data.
Presenting Coral, a paradigm that infers generative model structure, significantly reducing the amount of data required to learn structure.
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