Proximal support tensor machines

  • Reshma Khemchandani
  • Anuj Karpatne
  • Suresh Chandra
Original Article

Abstract

To utilize the structural information present in multidimensional features of an object, a tensor-based learning framework, termed as support tensor machines (STMs), was developed on the lines of support vector machines. In order to improve it further we have developed a least squares variant of STM, termed as proximal support tensor machine (PSTM), where the classifier is obtained by solving a system of linear equations rather than a quadratic programming problem at each iteration of PSTM algorithm as compared to STM algorithm. This in turn provides a significant reduction in the computation time, as well as comparable classification accuracy. The efficacy of the proposed method has been demonstrated in simulations over face detection and handwriting recognition datasets.

Keywords

Support tensor machines Alternating projection Proximal support vector machines 

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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Reshma Khemchandani
    • 1
  • Anuj Karpatne
    • 2
  • Suresh Chandra
    • 2
  1. 1.RBS India Development CentreGurgaonIndia
  2. 2.Department of MathematicsIndian Institute of TechnologyHauz KhasIndia

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