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Found 3 papers, 1 papers with code
Fair inference on error-prone outcomes
Fair inference in supervised learning is an important and active area of research, yielding a range of useful methods to assess and account for fairness criteria when predicting ground truth targets.
Privacy-Preserving Generalized Linear Models using Distributed Block Coordinate Descent
We conclude that our method is a viable approach for vertically partitioned data analysis with a wide range of real-world applications.
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