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Empirical Inference Technical Report 2002

Kernel Dependency Estimation

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Empirical Inference
Andre Elisseeff
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Empirical Inference
Jason Weston
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Empirical Inference
Olivier Chapelle
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Empirical Inference
Bernhard Schölkopf
  • Director

We consider the learning problem of finding a dependency between a general class of objects and another, possibly different, general class of objects. The objects can be for example: vectors, images, strings, trees or graphs. Such a task is made possible by employing similarity measures in both input and output spaces using kernel functions, thus embedding the objects into vector spaces. Output kernels also make it possible to encode prior information and/or invariances in the loss function in an elegant way. We experimentally validate our approach on several tasks: mapping strings to strings, pattern recognition, and reconstruction from partial images.

Author(s): Weston, J. and Chapelle, O. and Elisseeff, A. and Schölkopf, B. and Vapnik, V.
Number (issue): 98
Year: 2002
Month: August
Day: 0
Bibtex Type: Technical Report (techreport)
Digital: 0
Electronic Archiving: grant_archive
Institution: Max Planck Institute for Biological Cybernetics
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik
Links:

BibTex 

@techreport{1864,
  title = {Kernel Dependency Estimation},
  abstract = {We consider the learning problem of finding a dependency between a general class of objects and another, possibly different, general class of objects. The objects can be for example: vectors, images, strings, trees or graphs. Such a task is made possible by employing similarity measures in both input and output spaces using kernel functions, thus embedding the objects into vector spaces. Output kernels also make it possible to encode prior information and/or invariances in the loss function in an elegant way. We experimentally validate our approach on several tasks: mapping strings to strings, pattern recognition, and reconstruction from partial images.},
  number = {98},
  organization = {Max-Planck-Gesellschaft},
  institution = {Max Planck Institute for Biological Cybernetics},
  school = {Biologische Kybernetik},
  month = aug,
  year = {2002},
  slug = {1864},
  author = {Weston, J. and Chapelle, O. and Elisseeff, A. and Sch{\"o}lkopf, B. and Vapnik, V.},
  month_numeric = {8}
}