SVM Optimization: Inverse Dependence on Training Set Size
published: July 24, 2008, recorded: July 2008, views: 4677
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
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.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !