Deep Learning using Linear Support Vector Machines

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Deep Learning using Linear Support Vector MachinesYichuan of Computer Science, University of Toronto. Toronto, Ontario, , fully-connected and convolutionalneural networks have been trained to achievestate-of-the-art performance on a wide vari-ety of tasks such as speech recognition, im-age classification, natural language process-ing, and bioinformatics. For classificationtasks, most of these deep Learning modelsemploy the softmax activation function forprediction and minimize cross-entropy this paper, we demonstrate a small butconsistent advantage of replacing the soft-max layer with a Linear Support Vector ma-chine.

Deep Learning using Linear Support Vector Machines neural nets for classi cation. Lower layer weights are learned by backpropagating the gradients from the top

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