Optimization methods for regularized convex formulations in machine learning

We develop efficient numerical optimization algorithms for regularized convex formulations that appear in a variety of areas such as machine learning, statistics, and signal processing. Their objective functions consist of a loss term and a regularization term, where the latter controls the complexi...

Ausführliche Beschreibung

Bibliographische Detailangaben

1. Verfasser:	Lee, Sang Kyun
Format:	Dissertation
Sprache:	Englisch
Veröffentlicht:	ProQuest Dissertations & Theses 01.01.2011
Schlagworte:	Computer science
ISBN:	9781267055095, 126705509X
Online-Zugang:	Volltext
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