Incremental learning with ordinal bounded example memory

Authors:
Lorenzo Carlucci
Affiliations:
Department of Computer Science, University of Rome "La Sapienza", Roma, Italy
Venue:
ALT'09 Proceedings of the 20th international conference on Algorithmic learning theory
Year:
2009

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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 setdriven 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.