Systems that learn: an introduction to learning theory for cognitive and computer scientists
Systems that learn: an introduction to learning theory for cognitive and computer scientists
Recursively enumerable sets and degrees
Recursively enumerable sets and degrees
On the role of procrastination in machine learning
Information and Computation
Learning by switching type of information
Information and Computation
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Let Exdenote the explanatory model of learning [3,5]. Various more restrictive models have been studied in the literature, an example is finite identification [5]. The topic of the present paper are the natural variants (a) and (b) below of the classical question whether a given learning criteria is more restrictive than Ex-learning. (a) Does every infinite Ex-identifiable class have an infinite subclass which can be identified according to a given restrictive criterion? (b) If an infinite Exidentifiable class S has an infinite finitely identifiable subclass, does it necessarily follow that some appropriate learner Ex-identifies S as well as finitely identifies an infinite subclass of S? These questions are also treated in the context of ordinal mind change bounds.