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SVM Optimization: Inverse Dependence on Training Set Size

SVM Optimization: Inverse Dependence on Training Set Size

This video was recorded at 25th International Conference on Machine Learning (ICML), Helsinki 2008. We discuss how the runtime of SVM optimization should decrease as the size of the training data increases. We present theoretical and empirical results demonstrating how a simple subgradient descent approach indeed displays such behavior, at least for linear kernels.

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