We present some learning theory results on vector-valued reproducing kernel Hilbert space (RKHS) regression, where the input space is allowed to be non-compact and the output space is a (possibly infinite-dimensional) Hilbert space.

翻译：我们展示了一些关于矢量价值的复制内核Hilbert空间(RKHS)回归的学习理论结果,允许输入空间不兼容,输出空间(可能无限)Hilbert空间。