79 citations · 158 across the 15 of their papers we have counts for
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cs.CL2019
Semi-supervised Stochastic Multi-Domain Learning using Variational Inference
Yitong Li, Timothy Baldwin, Trevor Cohn
Supervised models of NLP rely on large collections of text which closely resemble the intended testing setting. Unfortunately matching text is often not available in sufficient qua…
cs.CR2019
Towards Fair and Privacy-Preserving Federated Deep Models
Lingjuan Lyu, Jiangshan Yu, Karthik Nandakumar +5
The current standalone deep learning framework tends to result in overfitting and low utility. This problem can be addressed by either a centralized framework that deploys a centra…