R O A
 VIEW ROA 917 
GO

917-0607 
Gradual learning and convergence
Author 
Joe Pater UMass Amherst <pater@linguist.umass.edu> [Details]
Comment 
To appear in Linguistic Inquiry
Length 
17 pp.
Files 
 PDF 258kb
Abstract 


This squib presents a simple abstract learning problem on which the Gradual Learning Algorithm (GLA; Boersma 1998, Boersma and Hayes 2001) fails. It then discusses the relationship of the GLA to the provably convergent Perceptron learning algorithm (Rosenblatt 1958), and shows that the learning problem is solved by a combination of the Perceptron update rule with Harmonic Grammar (Smolensky and Legendre 2006).
Keywords 
 learnability theory, harmonic grammar, GLA
Area 
 Phonology, Learnability
Type 
 Squib
 JUMP TO GO  
 Item Display:



R O A