Diplomarbeit DIP-3353

Bibliograph.
Daten
Rodriguez, Daniel del Hoyo: Optimization of Back-propagtion Learning Algorithm on MLP Networks.
Universität Stuttgart, Fakultät Informatik, Elektrotechnik und Informationstechnik, Diplomarbeit Nr. 3353 (2012).
95 Seiten, englisch.
CR-Klassif.D.1.3 (Concurrent Programming)
I.2.6 (Artificial Intelligence Learning)
Kurzfassung

Abstract ================================= In order to generate more efficient neural networks, the configuration of the ANN itself has to be optimized, specially refering to its parameters and architecture. To do so, this problem will be approached from the learning and training process point of view, realizing different tests. These evaluations will lead us to determine which are the most optimum parameters for this processes. At the same time, the importance of the input pattern and the data used will be studied, observing how these influences on the learning process, not only from a runtime point of view, but also measuring the obtained error in the trained network.

On the other side, the implementation itself will be optimized, doing this by executing the learning algorithm in parallel, using different nodes, meassuring the time needed for completing the trainning, and comparing it with the time needed in a sequential execution.

Volltext und
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Abteilung(en)Universität Stuttgart, Institut für Parallele und Verteilte Systeme, Verteilte Systeme
BetreuerZweigle Oliver; Glass Colin W.
Eingabedatum5. Dezember 2012
   Publ. Abteilung   Publ. Institut   Publ. Informatik