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  1. No Access

    Chapter and Conference Paper

    Learning Depth from Stereo

    We compare two approaches to the problem of estimating the depth of a point in space from observing its image position in two different cameras: 1. The classical photogrammetric approach explicitly models the ...

    Fabian H. Sinz, Joaquin Quiñonero Candela, Gökhan H. Bakır… in Pattern Recognition (2004)

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    Chapter and Conference Paper

    Multivariate Regression via Stiefel Manifold Constraints

    We introduce a learning technique for regression between high-dimensional spaces. Standard methods typically reduce this task to many one-dimensional problems, with each output dimension considered independent...

    Gökhan H. Bakır, Arthur Gretton, Matthias Franz, Bernhard Schölkopf in Pattern Recognition (2004)

  3. No Access

    Chapter and Conference Paper

    Learning to Find Graph Pre-images

    The recent development of graph kernel functions has made it possible to apply well-established machine learning methods to graphs. However, to allow for analyses that yield a graph as a result, it is necessar...

    Gökhan H. Bakır, Alexander Zien, Koji Tsuda in Pattern Recognition (2004)