Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
426726 | Information and Computation | 2016 | 17 Pages |
Abstract
The present work investigates the relationship of iterative learning with other learning criteria such as decisiveness, caution, reliability, non-U-shapedness, monotonicity, strong monotonicity and conservativeness. Building on the result of Case and Moelius that iterative learners can be made non-U-shaped, we show that they also can be made cautious and decisive. Furthermore, we obtain various special results with respect to one-one texts, fat texts and one-one hypothesis spaces.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Sanjay Jain, Timo Kötzing, Junqi Ma, Frank Stephan,