• For further details and the extension to multiclass settings we refer the reader to [4]. ()
  • SVM is a state-of-the-art large margin classifier, where the optimal separating surface is defined by a linear combination of scalar products between the view to be classified and some support vectors [6, 4]. ()
  • Specifically, we focus our attention on two algorithms: Support Vector Machines (SVM) [4] and Spin GlassMarkov Random Fields (SG-MRF) [5]. ()
  • b are found by using an SVC learning algorithm [4]. ()


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