Regularization Approaches to Learning Theory
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چکیده
This report is a self contained description of the results obtained during the second year of PhD and the plan for future work.
منابع مشابه
Regularization approaches for support vector machines with applications to biomedical data
The support vector machine (SVM) is a widely used machine learning tool for classification based on statistical learning theory. Given a set of training data, the SVM finds a hyperplane that separates two different classes of data points by the largest distance. While the standard form of SVM uses L2-norm regularization, other regularization approaches are particularly attractive for biomedical...
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Regularization is a well-recognized powerful strategy to improve the performance of a learning machine and l(q) regularization schemes with 0 < q < ∞ are central in use. It is known that different q leads to different properties of the deduced estimators, say, l(2) regularization leads to a smooth estimator, while l(1) regularization leads to a sparse estimator. Then how the generalization capa...
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تاریخ انتشار 2004