受强制性开放获取政策约束的文章 - Sumon Biswas了解详情
可在其他位置公开访问的文章：9 篇
Do the machine learning models on a crowd sourced platform exhibit bias? an empirical study on model fairness
S Biswas, H Rajan
Proceedings of the 28th ACM joint meeting on European software engineering …, 2020
强制性开放获取政策： US National Science Foundation
Fair preprocessing: towards understanding compositional fairness of data transformers in machine learning pipeline
S Biswas, H Rajan
Proceedings of the 29th ACM Joint Meeting on European Software Engineering …, 2021
强制性开放获取政策： US National Science Foundation
The art and practice of data science pipelines: A comprehensive study of data science pipelines in theory, in-the-small, and in-the-large
S Biswas, M Wardat, H Rajan
Proceedings of the 44th International Conference on Software Engineering …, 2022
强制性开放获取政策： US National Science Foundation
Towards Understanding Fairness and its Composition in Ensemble Machine Learning
U Gohar, S Biswas, H Rajan
In 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE …, 2023
强制性开放获取政策： US National Science Foundation
Fairify: Fairness verification of neural networks
S Biswas, H Rajan
2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE …, 2023
强制性开放获取政策： US National Science Foundation
Fix Fairness, Don't Ruin Accuracy: Performance Aware Fairness Repair using AutoML
G Nguyen, S Biswas, H Rajan
Proceedings of the 31st ACM joint meeting on European software engineering …, 2023
强制性开放获取政策： US National Science Foundation
23 shades of self-admitted technical debt: An empirical study on machine learning software
D OBrien, S Biswas, S Imtiaz, R Abdalkareem, E Shihab, H Rajan
Proceedings of the 30th ACM Joint European Software Engineering Conference …, 2022
强制性开放获取政策： US National Science Foundation
Are Prompt Engineering and TODO Comments Friends or Foes? An Evaluation on GitHub Copilot
D OBrien, S Biswas, SM Imtiaz, R Abdalkareem, E Shihab, H Rajan
2024 IEEE/ACM 46th International Conference on Software Engineering (ICSE), 2024
强制性开放获取政策： US National Science Foundation
Towards Safe ML-Based Systems in Presence of Feedback Loops
S Biswas, Y She, E Kang
Proceedings of the 1st International Workshop on Dependability and …, 2023
强制性开放获取政策： US National Science Foundation
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