Stochastic gradient versus recursive least squares learning

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SYSNO ASEP	0041991
Document Type	J - Journal Article
R&D Document Type	Journal Article
Subsidiary J	Ostatní články
Title	Stochastic gradient versus recursive least squares learning
Title	Proces učení: stochastický gradient versus rekurzivní nejmenší čtverce
Author(s)	Slobodyan, Sergey (NHU-N)_RID Bogomolova, Anna (NHU-N) Kolyuzhnov, Dmitri (NHU-N)_RID
Source Title	CERGE-EI Working Paper Series - ISSN 1211-3298 -, č. 309 (2006), s. 1-21
Number of pages	21 s.
Publication form	WWW - WWW
Language	eng - English
Country	CZ - Czech Republic
Keywords	constant gain adaptive learning ; stochastic gradient learning ; recursive least squares
Subject RIV	AH - Economics
CEZ	AV0Z70850503 - NHU-N (2005-2011)
Annotation	In this paper, we perform an in—depth investigation of relative merits of two adaptive learning algorithms with constant gain, Recursive Least Squares (RLS) and Stochastic Gradient (SG), using the Phelps model of monetary policy as a testing ground.
Workplace	Economics Institute
Contact	Tomáš Pavela, pavela@cerge-ei.cz, Tel.: 224 005 122
Year of Publishing	2007

Number of the records: 1