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.

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