Data Programming: Creating Large Training Sets, Quickly

Alexander J. Ratner, Christopher M. De Sa, Sen Wu, Daniel Selsam, Christopher Ré

Neural Information Processing Systems 

One further motivation for our method is driven by the observation that users often struggle with selecting features for their models, which is a traditional development bottleneck given fixed-size training sets.

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