Exponentiated Gradient versus Gradient Descent for Linear Predictors

We consider two algorithms for on-line prediction based on a linear model. The algorithms are the well-known gradient descent (GD) algorithm and a new algorithm, which we call EG ±. They both maintain a weight vector using simple updates. For the GD algorithm, the update is based on subtracting the...

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Veröffentlicht in:	Information and computation Jg. 132; H. 1; S. 1 - 63
Hauptverfasser:	Kivinen, Jyrki, Warmuth, Manfred K.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	San Diego, CA Elsevier Inc 10.01.1997 Elsevier
Schlagworte:	Algorithmics. Computability. Computer arithmetics Applied sciences Artificial intelligence Computer science; control theory; systems Exact sciences and technology Learning and adaptive systems Theoretical computing Learning Linear prediction Algorithms Gradient method Descent method On line processing
ISSN:	0890-5401, 1090-2651
Online-Zugang:	Volltext
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