5 citations · 9 across the 12 of their papers we have counts for
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cs.FL2020
Learning Languages in the Limit from Positive Information with Finitely Many Memory Changes
Timo Kötzing, Karen Seidel
We investigate learning collections of languages from texts by an inductive inference machine with access to the current datum and a bounded memory in form of states. Such a bounde…
cs.LG2020
Learning Half-Spaces and other Concept Classes in the Limit with Iterative Learners
Ardalan Khazraei, Timo Kötzing, Karen Seidel
In order to model an efficient learning paradigm, iterative learning algorithms access data one by one, updating the current hypothesis without regress to past data. Past research…