Online Learning versus Offline Learning

Shai Ben-David, Eyal Kushilevitz, Yishay Mansour

Research output: Contribution to journalArticlepeer-review

44 Scopus citations

Abstract

We present an off-line variant of the mistake-bound model of learning. This is an intermediate model between the on-line learning model (Littlestone, 1988, Littlestone, 1989) and the self-directed learning model (Goldman, Rivest & Schapire, 1993, Goldman & Sloan, 1994). Just like in the other two models, a learner in the off-line model has to learn an unknown concept from a sequence of elements of the instance space on which it makes "guess and test" trials. In all models, the aim of the learner is to make as few mistakes as possible. The difference between the models is that, while in the on-line model only the set of possible elements is known, in the off-line model the sequence of elements (i.e., the identity of the elements as well as the order in which they are to be presented) is known to the learner in advance. On the other hand, the learner is weaker than the self-directed learner, which is allowed to choose adaptively the sequence of elements presented to him. We study some of the fundamental properties of the off-line model. In particular, we compare the number of mistakes made by the off-line learner on certain concept classes to those made by the on-line and self-directed learners. We give bounds on the possible gaps between the various models and show examples that prove that our bounds are tight. Another contribution of this paper is the extension of the combinatorial tool of labeled trees to a unified approach that captures the various mistake bound measures of all the models discussed. We believe that this tool will prove to be useful for further study of models of incremental learning.

Original languageEnglish
Pages (from-to)45-63
Number of pages19
JournalMachine Learning
Volume29
Issue number1
DOIs
StatePublished - 1997

Funding

FundersFunder number
Japan Technion Society
Israel Academy of Sciences and Humanities
Israel Science Foundation
Ministry of Science and Technology, Israel
Technion-Israel Institute of Technology

    Keywords

    • Mistake-Bound
    • On-Line Learning
    • Rank of Trees

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