Search for: [Abstract = "We present a primal sub\-gradient method for structured SVM optimization defined with the averaged sum of hinge losses inside each example. Compared with the mini\-batch version of the Pegasos algorithm for the structured case, which deals with a single structure from each of multiple examples, our algorithm considers multiple structures from a single example in one update. This approach should increase the amount of information learned from the example."]

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