Abstract
A Bounded Example Memory learner is a learner that operates incrementally and maintains a memory of finitely many data items. The paradigm is well-studied and known to coincide with set-driven learning. A hierarchy of stronger and stronger learning criteria is obtained when one considers, for each k ∈ N, iterative learners that can maintain a memory of at most k previously processed data items. We report on recent investigations of extensions of the Bounded Example Memory model where a constructive ordinal notation is used to bound the number of times the learner can ask for proper global memory extensions.
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Carlucci, L. (2009). Incremental Learning with Ordinal Bounded Example Memory. In: Gavaldà, R., Lugosi, G., Zeugmann, T., Zilles, S. (eds) Algorithmic Learning Theory. ALT 2009. Lecture Notes in Computer Science(), vol 5809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04414-4_27
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DOI: https://doi.org/10.1007/978-3-642-04414-4_27
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