Search Results for author:
Found 2 papers, 2 papers with code
Learning Alternative Ways of Performing a Task
We evaluate the inferred models with respect to two metrics that measure how well the models represent the examples and capture the different forms of executing a task showed by the examples.
Fairness and Missing Values
To support this claim, (1) we analyse the sources of missing data and bias, and we map the common causes, (2) we find that rows containing missing values are usually fairer than the rest, which should not be treated as the uncomfortable ugly data that different techniques and libraries get rid of at the first occasion, and (3) we study the trade-off between performance and fairness when the rows with missing values are used (either because the technique deals with them directly or by imputation methods).
Cannot find the paper you are looking for? You can
Submit a new open access paper.
