مقاله برنامه های افزودنی خارج از نمونه برای روش های هسته غیر پارامتریک

عنوان مقاله فارسی: برنامه های افزودنی خارج از نمونه برای روش های هسته غیر پارامتریک عنوان مقاله لاتین: Out-of-Sample Extensions for Non-Parametric Kernel Methods نویسندگان: Binbin Pan; Wen-Sheng Chen; Bo Chen; Chen Xu; Jianhuang Lai تعداد صفحات: 11 سال انتشار: 2017 زبان: لاتین Abstract: Choosing suitable kernels plays an important role in the performance of kernel methods. Recently, a number of studies were devoted to developing nonparametric kernels. Without assuming any parametric form of the target kernel, nonparametric kernel learning offers a flexible scheme to utilize the information of the data, which may potentially characterize the data similarity better. The kernel methods using nonparametric kernels are referred to as nonparametric kernel methods. However, many nonparametric