Corpus ID: 5695599

A Statistical Test for Joint Distributions Equivalence

@article{Solera2016AST,
  title={A Statistical Test for Joint Distributions Equivalence},
  author={Francesco Solera and A. Palazzi},
  journal={ArXiv},
  year={2016},
  volume={abs/1607.07270}
}
  • Francesco Solera, A. Palazzi
  • Published 2016
  • Computer Science, Mathematics
  • ArXiv
  • We provide a distribution-free test that can be used to determine whether any two joint distributions $p$ and $q$ are statistically different by inspection of a large enough set of samples. Following recent efforts from Long et al. [1], we rely on joint kernel distribution embedding to extend the kernel two-sample test of Gretton et al. [2] to the case of joint probability distributions. Our main result can be directly applied to verify if a dataset-shift has occurred between training and test… CONTINUE READING
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    References

    SHOWING 1-10 OF 10 REFERENCES
    A Kernel Two-Sample Test
    • 1,769
    • Highly Influential
    • PDF
    A Kernel Method for the Two-Sample-Problem
    • 1,212
    • PDF
    A Hilbert Space Embedding for Distributions
    • 577
    • PDF
    Deep Transfer Learning with Joint Adaptation Networks
    • 697
    • Highly Influential
    • PDF
    Kernel Measures of Conditional Dependence
    • 367
    • PDF
    Rademacher and Gaussian Complexities: Risk Bounds and Structural Results
    • 1,703
    • PDF
    On the method of bounded differences. Surveys in combinatorics
    • On the method of bounded differences. Surveys in combinatorics
    • 1989
    Surveys in Combinatorics, 1989: On the method of bounded differences
    • 1,591