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Robust Learning Aided by Context

✍ Scribed by John Case; Sanjay Jain; Matthias Ott; Arun Sharma; Frank Stephan

Publisher: Elsevier Science
Year: 2000
Tongue: English
Weight: 207 KB
Volume: 60
Category: Article
ISSN: 0022-0000
DOI: 10.1006/jcss.1999.1637

No coin nor oath required. For personal study only.

✦ Synopsis

Empirical studies of multitask learning provide some evidence that the performance of a learning system on its intended targets improves by presenting to the learning system related tasks, also called contexts, as additional input. Angluin, Gasarch, and Smith, as well as Kinber, Smith, Velauthapillai, and Wiehagen, have provided mathematical justification for this phenomenon in the inductive inference framework. However, their proofs rely heavily on selfreferential coding tricks; that is, they directly code the solution of the learning problem into the context. Fulk has shown that for the Ex-and Bc-anomaly

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