A hierarchical k-NN search tree based on self-organizing maps retrieves MNIST neighbors about 800 times faster than exhaustive search, with error rising from 3.69% to 5.64%, and the same structure is shown on a toy translation task.
Gender shades: Intersectional accuracy disparities in commercial gender classification,
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Novel Approaches to Artificial Intelligence Development Based on the Nearest Neighbor Method
A hierarchical k-NN search tree based on self-organizing maps retrieves MNIST neighbors about 800 times faster than exhaustive search, with error rising from 3.69% to 5.64%, and the same structure is shown on a toy translation task.