Robust Learning of Deep Predictive Models from Noisy and Imbalanced Software Engineering Datasets

Author:

Li Zhong1ORCID,Pan Minxue1ORCID,Pei Yu2ORCID,Zhang Tian1ORCID,Wang Linzhang1,Li Xuandong1ORCID

Affiliation:

1. Nanjing University, China

2. The Hong Kong Polytechnic University, China

Publisher

ACM

Reference67 articles.

1. Hervé Abdi 2007. Bonferroni and Šidák corrections for multiple comparisons. Encyclopedia of measurement and statistics 3 ( 2007 ), 103–107. Hervé Abdi 2007. Bonferroni and Šidák corrections for multiple comparisons. Encyclopedia of measurement and statistics 3 (2007), 103–107.

2. Yingbin Bai Erkun Yang Bo Han Yanhua Yang Jiatong Li Yinian Mao Gang Niu and Tongliang Liu. 2021. Understanding and Improving Early Stopping for Learning with Noisy Labels. CoRR abs/2106.15853(2021). arXiv:2106.15853https://arxiv.org/abs/2106.15853 Yingbin Bai Erkun Yang Bo Han Yanhua Yang Jiatong Li Yinian Mao Gang Niu and Tongliang Liu. 2021. Understanding and Improving Early Stopping for Learning with Noisy Labels. CoRR abs/2106.15853(2021). arXiv:2106.15853https://arxiv.org/abs/2106.15853

3. Robust supervised classification with mixture models: Learning from data with uncertain labels

4. Class Imbalance Evolution and Verification Latency in Just-in-Time Software Defect Prediction

5. Kaidi Cao , Colin Wei , Adrien Gaidon , Nikos Aréchiga , and Tengyu Ma . 2019 . Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss. In Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019 , NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, Hanna M. Wallach, Hugo Larochelle, Alina Beygelzimer, Florence d’Alché-Buc, Emily B. Fox, and Roman Garnett (Eds.). 1565–1576. https://proceedings.neurips.cc/paper/2019/hash/621461af90cadfdaf0e8d4cc25129f91-Abstract.html Kaidi Cao, Colin Wei, Adrien Gaidon, Nikos Aréchiga, and Tengyu Ma. 2019. Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss. In Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, Hanna M. Wallach, Hugo Larochelle, Alina Beygelzimer, Florence d’Alché-Buc, Emily B. Fox, and Roman Garnett (Eds.). 1565–1576. https://proceedings.neurips.cc/paper/2019/hash/621461af90cadfdaf0e8d4cc25129f91-Abstract.html

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. DistXplore: Distribution-Guided Testing for Evaluating and Enhancing Deep Learning Systems;Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering;2023-11-30

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3