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Accuracy-Efficiency Trade-Offs and Accountability in Distributed ML Systems
4 July 2020
A. Feder Cooper
K. Levy
Christopher De Sa
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ArXiv (abs)
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Papers citing
"Accuracy-Efficiency Trade-Offs and Accountability in Distributed ML Systems"
3 / 3 papers shown
Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy and Research
A. Feder Cooper
Christopher A. Choquette-Choo
Miranda Bogen
Matthew Jagielski
Katja Filippova
...
Hanna M. Wallach
Amy Cyphert
Katherine Lee
Nicolas Papernot
Katherine Lee
MU
AILaw
357
29
0
09 Dec 2024
LOAM: Low-latency Communication, Caching, and Computation Placement in Data-Intensive Computing Networks
Jinkun Zhang
Edmund Yeh
191
2
0
23 Mar 2024
Accountability in an Algorithmic Society: Relationality, Responsibility, and Robustness in Machine Learning
Conference on Fairness, Accountability and Transparency (FAccT), 2022
A. Feder Cooper
Emanuel Moss
Benjamin Laufer
Helen Nissenbaum
MLAU
294
112
0
10 Feb 2022
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