Deep Text Mining of Instagram Data Without Strong Supervision
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.
Snorkel: Fast Training Set Generation for Information Extraction
Introducing Snorkel, a new system for quickly creating, managing, and modeling training datasets.
Learning to Compose Domain-Specific Transformations for Data Augmentation
Automating data augmentation by learning a generative sequence model over user-specified transformation functions.
Learning the Structure of Generative Models Without Labeled Data
Proposing a structure estimation method that is 100x faster than a maximum likelihood approach for training data.
Inferring Generative Model Structure With Static Analysis
Presenting Coral, a paradigm that infers generative model structure, significantly reducing the amount of data required to learn structure.
Data Programming: Creating Large Training Sets, Quickly
A paradigm for labeling training datasets programmatically rather than by hand.
Data Programming With DDLite: Putting Humans in a Different Part of the Loop
Introducing DDLite, an interactive development framework for data programming.