Fast Intersection / Additive Kernel SVMs

Subhransu Maji, Alexander C. Berg and Jitendra Malik



Below is a C++/MATLAB implementation of the fast Intersection Kernel SVM classifier described in the paper:

Classification Using Intersection Kernel Support Vector Machines is efficient.
Subhransu Maji and Alexander C. Berg and Jitendra Malik.
In Proceedings, CVPR 2008, Anchorage, Alaska.
pdf

The source code is available as a tar.gz

  • (2/2/11) fast-additive-svms.tar.gz | README
    • Includes libsvm-mat-3.0-1 : latest version of LIBSVM at the time of release.
    • Support for learning models using the intersection, chisquared, and JS kernel.
    • Fast approximate classification for these kernels using piecewise linear approximations. ONLY piecewise linear approximations are supported. The binary search based exact classification for intersection kernel is no longer supported.
    • C/C++ based mex code for picewise linear interpolation, weighted kernel sampling and a fast binary search based weighted intersection kernel sampling.
  • (7/10/09) libsvm-mat-2.8.1-fast.v3.tar.gz
    • Support for float/double features.
    • Precomputation and prediction are now separate modules. Lightweight approximate models can be precomputed and stored without the need to store all the support vectors.
    • Approximate(or exact) predictions can be done directly using the approximate(or exact) precomputed models.
    • Check out the README/READMEFAST for documentation.
  • (05/19/08) libsvm-mat-2.8.1-fast.tar.gz