5 citations · 5 across the 1 of their papers we have counts for
3 papers
cs.CL2020
A Simple but Tough-to-Beat Data Augmentation Approach for Natural Language Understanding and Generation
Dinghan Shen, Mingzhi Zheng, Yelong Shen +2
Adversarial training has been shown effective at endowing the learned representations with stronger generalization ability. However, it typically requires expensive computation to…
cs.CL2020
Improving Self-supervised Pre-training via a Fully-Explored Masked Language Model
Mingzhi Zheng, Dinghan Shen, Yelong Shen +2
Masked Language Model (MLM) framework has been widely adopted for self-supervised language pre-training. In this paper, we argue that randomly sampled masks in MLM would lead to un…
cs.LG2018★ 5 cited
Artificial neural networks condensation: A strategy to facilitate adaption of machine learning in medical settings by reducing computational burden
Dianbo Liu, Nestor Sepulveda, Ming Zheng
Machine Learning (ML) applications on healthcare can have a great impact on people's lives helping deliver better and timely treatment to those in need. At the same time, medical d…