How to Teach Support Vector Machine to Learn Vector Outputs

Posted in Science on August 08, 2008


How to Teach Support Vector Machine to Learn Vector Outputs

Lecture slides:

  • The “Classical” Support Vector Machine(SVM)
  • Reinterpretation of the normal vector w
  • Affine transformation = Linear transformation
  • Primal problem
  • Dual problem
  • Primal problem
  • Solution
  • Prediction
  • Prediction when the labels are implicit
  • Representation of multiclass output
  • Vertices of hyper-tetrahedron
  • Embedding Hierarchy
  • Methods
  • WIPO-alpha dataset
  • Computational times
  • Multiview learning
  • Primal problem
  • One-class SVM interpretation
  • Spherical embedding
  • Embedding Hierarchy
  • Similarities in a hierarchy
  • WIPO-alpha dataset
  • Primal problem
  • To get rid of occurrences of explicit labels ...
  • Prediction when the labels are implicit

Author: Sandor Szedmak, University of Southampton

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Tags: Science, Lectures, Computer Science, Machine Learning, VideoLectures.Net, Kernel Methods