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Keeping Deep Learning Models in Check: A History-Based Approach to Mitigate Overfitting

Jan 18, 2024
Hao Li, Gopi Krishnan Rajbahadur, Dayi Lin, Cor-Paul Bezemer, Zhen Ming, Jiang

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Studying the Practices of Testing Machine Learning Software in the Wild

Dec 19, 2023
Moses Openja, Foutse Khomh, Armstrong Foundjem, Zhen Ming, Jiang, Mouna Abidi, Ahmed E. Hassan

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Bug Characterization in Machine Learning-based Systems

Jul 26, 2023
Mohammad Mehdi Morovati, Amin Nikanjam, Florian Tambon, Foutse Khomh, Zhen Ming, Jiang

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GitHub Copilot AI pair programmer: Asset or Liability?

Jun 30, 2022
Arghavan Moradi Dakhel, Vahid Majdinasab, Amin Nikanjam, Foutse Khomh, Michel C. Desmarais, Zhen Ming, Jiang

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An Empirical Study of Challenges in Converting Deep Learning Models

Jun 28, 2022
Moses Openja, Amin Nikanjam, Ahmed Haj Yahmed, Foutse Khomh, Zhen Ming, Jiang

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Bugs in Machine Learning-based Systems: A Faultload Benchmark

Jun 24, 2022
Mohammad Mehdi Morovati, Amin Nikanjam, Foutse Khomh, Zhen Ming, Jiang

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Towards a Change Taxonomy for Machine Learning Systems

Mar 21, 2022
Aaditya Bhatia, Ellis E. Eghan, Manel Grichi, William G. Cavanagh, Zhen Ming, Jiang, Bram Adams

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Towards a consistent interpretation of AIOps models

Feb 04, 2022
Yingzhe Lyu, Gopi Krishnan Rajbahadur, Dayi Lin, Boyuan Chen, Zhen Ming, Jiang

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Towards Training Reproducible Deep Learning Models

Feb 04, 2022
Boyuan Chen, Mingzhi Wen, Yong Shi, Dayi Lin, Gopi Krishnan Rajbahadur, Zhen Ming, Jiang

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Can I use this publicly available dataset to build commercial AI software? Most likely not

Nov 09, 2021
Gopi Krishnan Rajbahadur, Erika Tuck, Li Zi, Zhang Wei, Dayi Lin, Boyuan Chen, Zhen Ming, Jiang, Daniel Morales German

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