Article ID Journal Published Year Pages File Type
4950734 Information and Computation 2016 15 Pages PDF
Abstract
We apply these techniques to show that, for set-driven and rearrangement-independent learning, any kind of U-shapes is unnecessary. Furthermore, we show that U-shapes are necessary in a strong way for iterative learning, contrasting with an earlier result by Case and Moelius that semantic U-shapes are unnecessary for iterative learning.
Related Topics
Physical Sciences and Engineering Computer Science Computational Theory and Mathematics
Authors
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