@techreport{2828,
  title = {Transductive Inference with Graphs},
  abstract = {We propose a general regularization framework for transductive
  inference. The given data are thought of as a graph, where the
  edges encode the pairwise relationships among data. We develop
  discrete analysis and geometry on graphs, and then naturally adapt
  the classical regularization in the continuous case to the graph
  situation. A new and effective algorithm is derived from this
  general framework,  as well as an approach we developed before.},
  organization = {Max-Planck-Gesellschaft},
  institution = {Max Planck Institute for Biological Cybernetics},
  school = {Biologische Kybernetik},
  year = {2004},
  note = {See the improved version Regularization on Discrete Spaces.},
  slug = {2828},
  author = {Zhou, D. and Sch{\"o}lkopf, B.}
}