Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.tcs.2009.02.013
Title: One-shot learners using negative counterexamples and nearest positive examples
Authors: Jain, S. 
Kinber, E.
Keywords: Counterexample
Inductive inference
Nearest positive example
Issue Date: 2009
Source: Jain, S., Kinber, E. (2009). One-shot learners using negative counterexamples and nearest positive examples. Theoretical Computer Science 410 (27-29) : 2562-2580. ScholarBank@NUS Repository. https://doi.org/10.1016/j.tcs.2009.02.013
Abstract: As some cognitive research suggests, in the process of learning languages, in addition to overt explicit negative evidence, a child often receives covert explicit evidence in form of corrected or rephrased sentences. In this paper, we suggest one approach to formalization of overt and covert evidence within the framework of one-shot learners via subset and membership queries to a teacher (oracle). We compare and explore general capabilities of our models, as well as complexity advantages of learnability models of one type over models of other types, where complexity is measured in terms of number of queries. In particular, we establish that "correcting" positive examples are sometimes more helpful to a learner than just negative (counter) examples and access to full positive data. © 2009 Elsevier B.V. All rights reserved.
Source Title: Theoretical Computer Science
URI: http://scholarbank.nus.edu.sg/handle/10635/39310
ISSN: 03043975
DOI: 10.1016/j.tcs.2009.02.013
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