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Memory limited inductive inference machines
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Memory limited inductive inference machines R sin Freivalds1 and Carl H. Smith2
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Institute of Mathematics and Computer Science, University of Latvia, Raina bulv ris 29, 226250 Riga, Latvia |
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Department of Computer Science and Institute for Advanced Computer Studies, The University of Maryland, 20742 College Park, MD, USA |
Abstract
The traditional model of learning in the limit is restricted so as to allow the learning machines only a fixed, finite amount of memory to store input and other data. A class of recursive functions is presented that cannot be learned deterministically by any such machine, but can be learned by a memory limited probabilistic leaning machine with probability 1.
Supported in part by NSF Grant CCR-9020079.
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