Proximal regularization for online and batch learning

• DOI: 10.1145/1553374.1553407
• Publication Date: 2009-06-16T13:34:36Z
• Authors: Chuong B. Do; Quoc V. Le; Chuan-Sheng Foo
• Keywords: Regularization

Many learning algorithms rely on the curvature (in particular, strong convexity) of regularized objective functions to provide good theoretical performance guarantees. In practice, choice regularization penalty that gives best testing set may result in with little or even no curvature. these cases, designed specifically for objectives often either fail completely require some modification involves a substantial compromise performance.