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Hilbert space embedding of probability distributions

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If you have a question about this talk, please contact Shakir Mohamed.

The seminar will focus on representing probability measures via mean elements in characteristic reproducing Hilbert spaces.

In particular I plan to talk about:
  • RKHS ’s and characteristic kernels in general
  • homogeneity and independence testing using RKH Ss
  • density estimation via kernel moment matching
Recommended reading:
  • Gretton et al: A Kernel Method for the Two-Sample Problem, NIPS ‘08, pdf
  • recently updated Song et al: Tailoring Density Estimation via Reproducing Kernel Moment Matching www
  • Gretton et al: Measuring Statistical Dependence with Hilbert Schmidt norms, ALT ’05, pdf
Further reading/material:
  • Gretton et al: MPI Technical report 157 about two-sample test pdf
  • Gretton et al, JMLR , 2005 pdf
  • Fukumizu et al, JMLR , 2004 pdf
  • Kenji Fukumizu’s lecture slides: www
  • Kenju Fukumizu’s tutorial at MLSS ’07: www

This talk is part of the Machine Learning Reading Group @ CUED series.

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