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http://dspace.mediu.edu.my:8181/xmlui/handle/10419/19040| Title: | Generalized stochastic gradient learning |
| Keywords: | C65 C62 E17 E10 D83 ddc:330 adaptive learning E-stability recursive least squares robust estimation Rationale Erwartung Lernprozess Prognoseverfahren Gleichgewichtsstabilität Theorie |
| Issue Date: | 16-Oct-2013 |
| Publisher: | |
| Description: | We study the properties of generalized stochastic gradient (GSG) learning in forward-looking models. We examine how the conditions for stability of standard stochastic gradient (SG) learning both differ from and are related to E-stability, which governs stability under least squares learning. SG algorithms are sensitive to units of measurement and we show that there is a transformation of variables for which E-stability governs SG stability. GSG algorithms with constant gain have a deeper justification in terms of parameter drift, robustness and risk sensitivity. |
| URI: | http://koha.mediu.edu.my:8181/xmlui/handle/10419/19040 |
| Other Identifiers: | http://hdl.handle.net/10419/19040 ppn:503712469 |
| Appears in Collections: | EconStor |
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