566 citations · 696 across the 4 of their papers we have counts for
4 papers
Generative Image Translation for Data Augmentation of Bone Lesion Pathology
Anant Gupta, Srivas Venkatesh, Sumit Chopra +1
Insufficient training data and severe class imbalance are often limiting factors when developing machine learning models for the classification of rare diseases. In this work, we a…
StarSpace: Embed All The Things!
Ledell Wu, Adam Fisch, Sumit Chopra +3
We present StarSpace, a general-purpose neural embedding model that can solve a wide variety of problems: labeling tasks such as text classification, ranking tasks such as informat…
Training Language Models Using Target-Propagation
Sam Wiseman, Sumit Chopra, Marc'Aurelio Ranzato +4
While Truncated Back-Propagation through Time (BPTT) is the most popular approach to training Recurrent Neural Networks (RNNs), it suffers from being inherently sequential (making…
Large-scale Simple Question Answering with Memory Networks
Antoine Bordes, Nicolas Usunier, Sumit Chopra +1
Training large-scale question answering systems is complicated because training sources usually cover a small portion of the range of possible questions. This paper studies the imp…