• Corpus ID: 250243739

Prediction of random variables by excursion metric projections

  title={Prediction of random variables by excursion metric projections},
  author={Vitalii Makogin and E. Spodarev},
We use the concept of excursions for the prediction of random variables without any moment existence assumption. To do so, an excursion metric on the space of random variables is defined which appears to be a kind of a weighted L 1 -distance. Using equivalent forms of this metric and a specific choice of excursion levels, we formulate the prediction problem as a minimization of a certain target functional. Existence and uniqueness of the solution are discussed. An application to the extrapolation… 



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Single-Image Super-Resolution Using Sparse Regression and Natural Image Prior

  • K. KimYounghee Kwon
  • Computer Science, Mathematics
    IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2010
Compared with existing algorithms, KRR leads to a better generalization than simply storing the examples as has been done in existing example-based algorithms and results in much less noisy images.