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pro vyhledávání: '"Yang, Tianling"'
Autor:
Miceli, Milagros, Yang, Tianling, Garcia, Adriana Alvarado, Posada, Julian, Wang, Sonja Mei, Pohl, Marc, Hanna, Alex
Publikováno v:
Proceedings of the ACM on Human-Computer Interaction, 6(CSCW2), 2022
The opacity of machine learning data is a significant threat to ethical data work and intelligible systems. Previous research has addressed this issue by proposing standardized checklists to document datasets. This paper expands that field of inquiry
Externí odkaz:
http://arxiv.org/abs/2207.04958
Research in machine learning (ML) has primarily argued that models trained on incomplete or biased datasets can lead to discriminatory outputs. In this commentary, we propose moving the research focus beyond bias-oriented framings by adopting a power
Externí odkaz:
http://arxiv.org/abs/2109.08131
The interpretation of data is fundamental to machine learning. This paper investigates practices of image data annotation as performed in industrial contexts. We define data annotation as a sense-making practice, where annotators assign meaning to da
Externí odkaz:
http://arxiv.org/abs/2007.14886
Akademický článek
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Autor:
Miceli, Milagros, Yang, Tianling, Garcia, Adriana Alvarado, Posada, Julian, Wang, Sonja Mei, Pohl, Marc, Hanna, Alex
Publikováno v:
Proceedings of the ACM on Human-Computer Interaction. 6:1-34
The opacity of machine learning data is a significant threat to ethical data work and intelligible systems. Previous research has addressed this issue by proposing standardized checklists to document datasets. This paper expands that field of inquiry
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::513715194960cdb6fd69bfdd63883b69
https://doi.org/10.1145/3555623
https://doi.org/10.1145/3555623
Autor:
Delobelle, Pieter, Scott, Kristen, Wang, Sonja Mei, Miceli, Milgros, Hartmann, David, Yang, Tianling, Murasso, Elena, Sztandar-Sztanderska, Karolina, Berendt, Bettina
ispartof: Online proceedings of the International workshop on Fair, Effective And Sustainable Talent management using data science ispartof: International workshop on Fair, Effective And Sustainable Talent management using data science at European Co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1131::70ec06fc277b535a73f230d80b718011
https://lirias.kuleuven.be/handle/123456789/679296
https://lirias.kuleuven.be/handle/123456789/679296
Autor:
Xu, Gang1 (AUTHOR) xugang619@hotmail.com, Yu, Yunhong1 (AUTHOR), Yang, Jingyao1 (AUTHOR), Wang, Tianling1 (AUTHOR), Kong, Peipei1 (AUTHOR), Chen, Xianhua1 (AUTHOR) chenxh@seu.edu.cn
Publikováno v:
Polymers (20734360). Sep2021, Vol. 13 Issue 18, p3037-3037. 1p.
Autor:
Semel, Beth M.
Publikováno v:
Science, Technology & Human Values; Mar2022, Vol. 47 Issue 2, p266-290, 25p
Publikováno v:
Health & Medicine Week; 2024, p6395-6395, 1p
Publikováno v:
Microwave & Optical Technology Letters; Nov2016, Vol. 58 Issue 11, p2657-2661, 5p