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

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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

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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

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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?

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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

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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

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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

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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

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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

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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

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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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