NIPS Proceedingsβ

Kenji Fukumizu

16 Papers

  • Gradient-based kernel method for feature extraction and variable selection (2012)
  • Learning from Distributions via Support Measure Machines (2012)
  • Optimal kernel choice for large-scale two-sample tests (2012)
  • Kernel Bayes' Rule (2011)
  • Learning in Hilbert vs. Banach Spaces: A Measure Embedding Viewpoint (2011)
  • A Fast, Consistent Kernel Two-Sample Test (2009)
  • Graph Zeta Function in the Bethe Free Energy and Loopy Belief Propagation (2009)
  • Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions (2009)
  • Characteristic Kernels on Groups and Semigroups (2008)
  • A Kernel Statistical Test of Independence (2007)
  • Kernel Measures of Conditional Dependence (2007)
  • Kernels on Structured Objects Through Nested Histograms (2006)
  • Statistical Convergence of Kernel CCA (2005)
  • Kernel Dimensionality Reduction for Supervised Learning (2003)
  • Critical Lines in Symmetry of Mixture Models and its Application to Component Splitting (2002)
  • Active Learning in Multilayer Perceptrons (1995)