We provide comprehensive experimental evaluation of our proposal, along with alternative design choices, on a standard Python dataset, as well as on a Python corpus internal to Facebook.
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We approach the problem of generalizing pre-trained word embeddings beyond fixed-size vocabularies without using additional contextual information.
We address the problem of discovering communication links between applications in the popular Android mobile operating system, an important problem for security and privacy in Android.
Distributed implementations of mini-batch stochastic gradient descent (SGD) suffer from communication overheads, attributed to the high frequency of gradient updates inherent in small-batch training.