95 citations · 147 across the 4 of their papers we have counts for
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cs.LG2019★ 95 cited
Interpretable and Steerable Sequence Learning via Prototypes
Yao Ming, Panpan Xu, Huamin Qu +1
One of the major challenges in machine learning nowadays is to provide predictions with not only high accuracy but also user-friendly explanations. Although in recent years we have…
cs.HC2019
Learning Vis Tools: Teaching Data Visualization Tutorials
Leo Yu-Ho Lo, Yao Ming, Huamin Qu
Teaching and advocating data visualization are among the most important activities in the visualization community. With growing interest in data analysis from business and science…
cs.LG2019
ATMSeer: Increasing Transparency and Controllability in Automated Machine Learning
Qianwen Wang, Yao Ming, Zhihua Jin +5
To relieve the pain of manually selecting machine learning algorithms and tuning hyperparameters, automated machine learning (AutoML) methods have been developed to automatically s…