• computational complexity of kernel-based density-ratio estimation: a condition number analysis

    جزئیات بیشتر مقاله
    • تاریخ ارائه: 1392/07/24
    • تاریخ انتشار در تی پی بین: 1392/07/24
    • تعداد بازدید: 1134
    • تعداد پرسش و پاسخ ها: 0
    • شماره تماس دبیرخانه رویداد: -
     in this study, the computational properties of a kernel-based least-squares density-ratio estimator are investigated from the viewpoint of condition numbers. the condition number of the hessian matrix of the loss function is closely related to the convergence rate of optimization and the numerical stability. we use smoothed analysis techniques and theoretically demonstrate that the kernel least-squares method has a smaller condition number than other m-estimators. this implies that the kernel least-squares method has desirable computational properties. in addition, an alternate formulation of the kernel least-squares estimator that possesses an even smaller condition number is presented. the validity of the theoretical analysis is verified through numerical experiments.

سوال خود را در مورد این مقاله مطرح نمایید :

با انتخاب دکمه ثبت پرسش، موافقت خود را با قوانین انتشار محتوا در وبسایت تی پی بین اعلام می کنم
مقالات جدیدترین رویدادها
مقالات جدیدترین ژورنال ها