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Christina Greer
Christina Greer
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Year
Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ...
arXiv preprint arXiv:2312.11805, 2023
5392023
Towards accountability for machine learning datasets: Practices from software engineering and infrastructure
B Hutchinson, A Smart, A Hanna, E Denton, C Greer, O Kjartansson, ...
Proceedings of the 2021 ACM Conference on Fairness, Accountability, and …, 2021
2762021
Evaluation gaps in machine learning practice
B Hutchinson, N Rostamzadeh, C Greer, K Heller, V Prabhakaran
Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022
372022
Measuring model biases in the absence of ground truth
O Aka, K Burke, A Bauerle, C Greer, M Mitchell
Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 327-335, 2021
312021
Introducing the model card toolkit for easier model transparency reporting
H Fang, H Miao, K Shukla, D Nanas, C Xu, C Greer, N Polyzotis, T Doshi, ...
Google AI Blog, 2020
152020
Thinking beyond distributions in testing machine learned models
N Rostamzadeh, B Hutchinson, C Greer, V Prabhakaran
arXiv preprint arXiv:2112.03057, 2021
52021
Visual Identification of Problematic Bias in Large Label Spaces
A Bäuerle, AG Turker, K Burke, O Aka, T Ropinski, C Greer, ...
arXiv preprint arXiv:2201.06386, 2022
32022
Towards accountability for machine learning datasets
A Hanna, A Smart, B Hutchinson, C Greer, E Denton, M Mitchell, ...
Proceedings of the Conference on Fairness, Accountability, and Transparency …, 2021
32021
Fairness Indicators Demo: Scalable Infrastructure for Fair ML Systems
C Xu, C Greer, MN Joshi, T Doshi
22020
Rethinking Testing of Machine Learned Models
N Rostamzadeh, B Hutchinson, V Prabhakaran, C Greer
2022
Critical Evaluation Gaps in Machine Learning Practice
B Hutchinson, K Heller, N Rostamzadeh, V Prabhakaran
2022
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