Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4950734 | Information and Computation | 2016 | 15 Pages |
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.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
John Case, Timo Kötzing,