54 citations · 73 across the 9 of their papers we have counts for
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cs.LG2021
Generalizing Neural Networks by Reflecting Deviating Data in Production
Yan Xiao, Yun Lin, Ivan Beschastnikh +3
Trained with a sufficiently large training and testing dataset, Deep Neural Networks (DNNs) are expected to generalize. However, inputs may deviate from the training dataset distri…
cs.SE2021
RegMiner: Towards Constructing a Large Regression Dataset from Code Evolution History
Xuezhi Song, Yun Lin, Siang Hwee Ng +4
Bug datasets consisting of real-world bugs are important artifacts for researchers and programmers, which lay empirical and experimental foundation for various SE/PL research such…
cs.LG2021★ 3 cited
Automatic Fairness Testing of Neural Classifiers through Adversarial Sampling
Peixin Zhang, Jingyi Wang, Jun Sun +5
Although deep learning has demonstrated astonishing performance in many applications, there are still concerns about its dependability. One desirable property of deep learning appl…