# #StackBounty: #svm #optimization The role of Support Vectors in optimization

### Bounty: 50

I believe that I have somewhat an understanding of the objective and loss functions associated with Support Vector Machines (SVM), however, one point is still confusing me: The fact that the margins of the SVM can be characterized only by the Support Vectors is often named as a reason for their efficient optimization.

What I do not understand is this: To know what the Support Vectors will be, doesn’t the algorithm have to consider all the datapoints in the beginning? I.e. is this sparse representation not only possible after training?

Get this bounty!!!

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