Please use this identifier to cite or link to this item:
|Title:||One-shot learners using negative counterexamples and nearest positive examples|
|Authors:||Jain, S. |
Nearest positive example
|Citation:||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|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on May 19, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.