A Least-squares Approach to Direct Importance Estimation

  title={A Least-squares Approach to Direct Importance Estimation},
  author={Takafumi Kanamori and Shohei Hido and Masashi Sugiyama},
  journal={Journal of Machine Learning Research},
We address the problem of estimating the ratio of two probabi lity density functions, which is often referred to as theimportance. The importance values can be used for various succeeding ta sks such ascovariate shift adaptationor outlier detection. In this paper, we propose a new importance estimation method that has a closed-form solution; the leav e-one-out cross-validation score can also be computed analytically. Therefore, the proposed method i s computationally highly efficient and simple… CONTINUE READING
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An algorithm for the solution of the parametric quadratic programmin

  • Athena Scientific, MA Belmont
  • 2003

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